The value of CT-based radiomics in predicting hemorrhagic transformation in acute ischemic stroke patients without recanalization therapy.

Objective: The aim of this study is to investigate the clinical value of radiomics based on non-enhanced head CT in the prediction of hemorrhage transformation in acute ischemic stroke (AIS). Materials and methods: A total of 140 patients diagnosed with AIS from January 2015 to August 2022 were enrolled. Radiomic features from infarcted areas on non-enhanced CT images were extracted using ITK-SNAP. The max-relevance and min-redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select features. The radiomics signature was then constructed by multiple logistic regressions. The clinicoradiomics nomogram was constructed by combining radiomics signature and clinical characteristics. All predictive models were constructed in the training group, and these were verified in the validation group. All models were evaluated with the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: Of the 140 patients, 59 experienced hemorrhagic transformation, while 81 remained stable. The radiomics signature was constructed by 10 radiomics features. The clinicoradiomics nomogram was constructed by combining radiomics signature and atrial fibrillation. The area under the ROC curve (AUCs) of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the training group were 0.64, 0.86, and 0.86, respectively. The AUCs of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the validation group were 0.63, 0.90, and 0.90, respectively. The DCA curves showed that the radiomics signature performed well as well as the clinicoradiomics nomogram. The DCA curve showed that the clinical application value of the radiomics signature is similar to that of the clinicoradiomics nomogram. Conclusion: The radiomics signature, constructed without incorporating clinical characteristics, can independently and effectively predict hemorrhagic transformation in AIS patients.

Dynamic Stereochemistry of M8 Pd6 Supramolecular Cages Based on Metal-Center Lability for Differential Chiral Induction, Resolution, and Recognition.

A series of isostructural supramolecular cages with a rhombic dodecahedron shape have been assembled with distinct metal-coordination lability (M8 Pd6 -MOC-16, M=Ru2+ , Fe2+ , Ni2+ , Zn2+ ). The chirality transfer between metal centers generally imposes homochirality on individual cages to enable solvent-dependent spontaneous resolution of Δ8 /Λ8 -M8 Pd6 enantiomers; however, their distinguishable stereochemical dynamics manifests differential chiral phenomena governed by the cage stability following the order Ru8 Pd6 >Ni8 Pd6 >Fe8 Pd6 >Zn8 Pd6 . The highly labile Zn centers endow the Zn8 Pd6 cage with conformational flexibility and deformation, enabling intrigue chiral-Δ8 /Λ8 -Zn8 Pd6 to meso-Δ4 Λ4 -Zn8 Pd6 transition induced by anions. The cage stabilization effect differs from inert Ru2+ , metastable Fe2+ /Ni2+ , and labile Zn2+ , resulting in different chiral-guest induction. Strikingly, solvent-mediated host-guest interactions have been revealed for Δ8 /Λ8 -(Ru/Ni/Fe)8 Pd6 cages to discriminate the chiral recognition of the guests with opposite chirality. These results demonstrate a versatile procedure to control the stereochemistry of metal-organic cages based on the dynamic metal centers, thus providing guidance to maneuver cage chirality at a supramolecular level by virtue of the solvent, anion, and guest to benefit practical applications.

Dynamic Metallosupramolecular Cages Containing 12 Adaptable Pockets for High-Order Guest Binding Beyond Biomimicry.

Molecular recognition lies at the heart of biological functions, which inspires lasting research in artificial host syntheses to mimic biomolecules that can recognize, process, and transport molecules with the highest level of complexity; nonetheless, the design principle and quantifying methodology of artificial hosts for multiple guests (≥4) remain a formidable task. Herein, we report two rhombic dodecahedral cages [(Zn/Fe)8Pd6-MOC-16], which embrace 12 adaptive pockets for multiguest binding with distinct conformational dynamics inherent in metal-center lability and are able to capture 4-24 guests to manifest a surprising complexity of binding scenarios. The exceptional high-order and hierarchical encapsulation phenomena suggest a wide host-guest dynamic-fit, enabling conformational adjustment and adaptation beyond the duality of induced-fit and conformational selection in protein interactions. A critical inspection of the host-guest binding events in solution has been performed by NMR and ESI-MS spectra, highlighting the importance of acquiring a reliable binding repertoire from different techniques and the uncertainty of quantifying the binding affinities of multiplying guests by an oversimplified method.

Radio- and Photosensitizing Os(II)-Based Nanocage for Combined Radio-/Chemo-/X-ray-Induced Photodynamic Therapies, NIR Imaging, and Drug Delivery.

Integration of clinical imaging and collaborative multimodal therapies into a single nanomaterial for multipurpose diagnosis and treatment is of great interest to theranostic nanomedicine. Here, we report a rational design of a discrete Os-based metal-organic nanocage Pd6(OsL3)828+ (MOC-43) as a versatile theranostic nanoplatform to meet the following demands simultaneously: (1) synergistic treatments of radio-, chemo-, and X-ray-induced photodynamic therapies (X-PDT) for breast cancer, (2) NIR imaging for cancer cell tracking and tumor-targeting, and (3) anticancer drug transport through a host-guest strategy. The nanoscale MOC-43 incorporates high-Z Os-element to interact with X-ray irradiation for dual radiosensitization and photosensitization, showing efficient energy transfer to endogenous oxygen in cancer cells to enhance X-PDT efficacy. It also features intrinsic NIR emission originating from metal-to-ligand charge transfer (MLCT) as an excellent imaging probe. Meanwhile, its 12 pockets can capture and concentrate low-water-soluble molecules for anticancer drug delivery. These multifunctions are implemented and demonstrated by micellization of coumarin-loaded cages with DSPE-PEG2000 into coumarin ⊂ MOC-43 nanoparticles (CMNPs) for efficient subcellular endocytosis and uptake. The cancer treatments in vitro/in vivo show promising antitumor performance, providing a conceptual protocol to combine cage-cargo drug transport with diagnosis and treatment for collaborative cancer theranostics by virtue of multifunction synergism on a single-nanomaterial platform.

RSU-Net: U-net based on residual and self-attention mechanism in the segmentation of cardiac magnetic resonance images.

BACKGROUND: Automated segmentation techniques for cardiac magnetic resonance imaging (MRI) are beneficial for evaluating cardiac functional parameters in clinical diagnosis. However, due to the characteristics of unclear image boundaries and anisotropic resolution anisotropy produced by cardiac magnetic resonance imaging technology, most of the existing methods still have the problems of intra-class uncertainty and inter-class uncertainty. However, due to the irregularity of the anatomical shape of the heart and the inhomogeneity of tissue density, the boundaries of its anatomical structures become uncertain and discontinuous. Therefore, fast and accurate segmentation of cardiac tissue remains a challenging problem in medical image processing. METHODOLOGY: We collected cardiac MRI data from 195 patients as training set and 35patients from different medical centers as external validation set. Our research proposed a U-net network architecture with residual connections and a self-attentive mechanism (Residual Self-Attention U-net, RSU-Net). The network relies on the classic U-net network, adopts the U-shaped symmetric architecture of the encoding and decoding mode, improves the convolution module in the network, introduces skip connections, and improves the network's capacity for feature extraction. Then for solving locality defects of ordinary convolutional networks. To achieve a global receptive field, a self-attention mechanism is introduced at the bottom of the model. The loss function employs a combination of Cross Entropy Loss and Dice Loss to jointly guide network training, resulting in more stable network training. RESULTS: In our study, we employ the Hausdorff distance (HD) and the Dice similarity coefficient (DSC) as metrics for assessing segmentation outcomes. Comparsion was made with the segmentation frameworks of other papers, and the comparison results prove that our RSU-Net network performs better and can make accurate segmentation of the heart. New ideas for scientific research. CONCLUSION: Our proposed RSU-Net network combines the advantages of residual connections and self-attention. This paper uses the residual links to facilitate the training of the network. In this paper, a self-attention mechanism is introduced, and a bottom self-attention block (BSA Block) is used to aggregate global information. Self-attention aggregates global information, and has achieved good segmentation results on the cardiac segmentation dataset. It facilitates the diagnosis of cardiovascular patients in the future.

Stroke risk study based on deep learning-based magnetic resonance imaging carotid plaque automatic segmentation algorithm.

Introduction: The primary factor for cardiovascular disease and upcoming cardiovascular events is atherosclerosis. Recently, carotid plaque texture, as observed on ultrasonography, is varied and difficult to classify with the human eye due to substantial inter-observer variability. High-resolution magnetic resonance (MR) plaque imaging offers naturally superior soft tissue contrasts to computed tomography (CT) and ultrasonography, and combining different contrast weightings may provide more useful information. Radiation freeness and operator independence are two additional benefits of M RI. However, other than preliminary research on MR texture analysis of basilar artery plaque, there is currently no information addressing MR radiomics on the carotid plaque. Methods: For the automatic segmentation of MRI scans to detect carotid plaque for stroke risk assessment, there is a need for a computer-aided autonomous framework to classify MRI scans automatically. We used to detect carotid plaque from MRI scans for stroke risk assessment pre-trained models, fine-tuned them, and adjusted hyperparameters according to our problem. Results: Our trained YOLO V3 model achieved 94.81% accuracy, RCNN achieved 92.53% accuracy, and MobileNet achieved 90.23% in identifying carotid plaque from MRI scans for stroke risk assessment. Our approach will prevent incorrect diagnoses brought on by poor image quality and personal experience. Conclusion: The evaluations in this work have demonstrated that this methodology produces acceptable results for classifying magnetic resonance imaging (MRI) data.

Cardiac MRI segmentation of the atria based on UU-NET.

Background and objective: In today's society, people's work pressure, coupled with irregular diet, lack of exercise and other bad lifestyle, resulting in frequent cardiovascular diseases. Medical imaging has made great progress in modern society, among which the role of MRI in cardiovascular field is self-evident. Based on this research background, how to process cardiac MRI quickly and accurately by computer has been extensively discussed. By comparing and analyzing several traditional image segmentation and deep learning image segmentation, this paper proposes the left and right atria segmentation algorithm of cardiac MRI based on UU-NET network. Methods: In this paper, an atrial segmentation algorithm for cardiac MRI images in UU-NET network is proposed. Firstly, U-shaped upper and lower sampling modules are constructed by using residual theory, which are used as encoders and decoders of the model. Then, the modules are interconnected to form multiple paths from input to output to increase the information transmission capacity of the model. Results: The segmentation method based on UU-NET network has achieved good results proposed in this paper, compared with the current mainstream image segmentation algorithm results have been improved to a certain extent. Through the analysis of the experimental results, the image segmentation algorithm based on UU-NET network on the data set, its performance in the verification set and online set is higher than other grid models. The DSC in the verification set is 96.7%, and the DSC in the online set is 96.7%, which is nearly one percentage point higher than the deconvolution neural network model. The hausdorff distance (HD) is 1.2 mm. Compared with other deep learning models, it is significantly improved (about 3 mm error is reduced), and the time is 0.4 min. Conclusion: The segmentation algorithm based on UU-NET improves the segmentation accuracy obviously compared with other segmentation models. Our technique will be able to help diagnose and treat cardiac complications.

Breast MRI Segmentation and Ki-67 High- and Low-Expression Prediction Algorithm Based on Deep Learning.

Results: The DSC, PPV, and sensitivity of our combined model are 0.94, 0.93, and 0.94, respectively, with better segmentation performance. And we compare with the segmentation frameworks of other papers and find that our combined model can make accurate segmentation of breast tumors. Conclusion: Our method can adapt to the variability of breast tumors and segment breast tumors accurately and efficiently. In the future, it can be widely used in clinical practice, so as to help the clinic better formulate a reasonable diagnosis and treatment plan for breast cancer patients.

Breast MRI Tumor Automatic Segmentation and Triple-Negative Breast Cancer Discrimination Algorithm Based on Deep Learning.

Background: Breast cancer is a kind of cancer that starts in the epithelial tissue of the breast. Breast cancer has been on the rise in recent years, with a younger generation developing the disease. Magnetic resonance imaging (MRI) plays an important role in breast tumor detection and treatment planning in today's clinical practice. As manual segmentation grows more time-consuming and the observed topic becomes more diversified, automated segmentation becomes more appealing. Methodology. For MRI breast tumor segmentation, we propose a CNN-SVM network. The labels from the trained convolutional neural network are output using a support vector machine in this technique. During the testing phase, the convolutional neural network's labeled output, as well as the test grayscale picture, is passed to the SVM classifier for accurate segmentation. Results: We tested on the collected breast tumor dataset and found that our proposed combined CNN-SVM network achieved 0.93, 0.95, and 0.92 on DSC coefficient, PPV, and sensitivity index, respectively. We also compare with the segmentation frameworks of other papers, and the comparison results prove that our CNN-SVM network performs better and can accurately segment breast tumors. Conclusion: Our proposed CNN-SVM combined network achieves good segmentation results on the breast tumor dataset. The method can adapt to the differences in breast tumors and segment breast tumors accurately and efficiently. It is of great significance for identifying triple-negative breast cancer in the future.

Enhancing anaerobic digestion of food waste with granular activated carbon immobilized with riboflavin.

Previous studies have shown that anaerobic digestion of food waste can be enhanced by addition of conductive materials that stimulate direct interspecies electron transfer (DIET) between bacteria and methanogens. However, at extremely high organic loading rates (OLRs), volatile fatty acids (VFAs) still tend to accumulate even in the presence of conductive materials because of an imbalance between the formation of fermentation products and the rate of methanogenesis. In this study, granular activated carbon (GAC) immobilized with riboflavin (GAC-riboflavin) was added to an anaerobic digester treating food waste. The GAC-riboflavin reactor operated stably at OLRs as high as 11.5 kgCOD/ (m3·d) and kept VFA concentrations below 69.4 mM, COD removal efficiencies, methane production rates, and biogas methane concentrations were much higher in the GAC-riboflavin reactor than the GAC- and non-amended reactors. Transcripts associated with genes that code for proteins involved in DIET based metabolism were somewhat more highly expressed by Methanothrix in the GAC-riboflavin reactor. However, it is unlikely that riboflavin acted as an electron shuttle to stimulate DIET. Rather, it seemed to provide nutrients that enhanced the growth of microorganisms involved in the anaerobic digestion process, including those that are capable of DIET.

A Redox-Active Supramolecular Fe4L6 Cage Based on Organic Vertices with Acid-Base-Dependent Charge Tunability for Dehydrogenation Catalysis.

Supramolecular cage chemistry is of lasting interest because, as artificial blueprints of natural enzymes, the self-assembled cage structures not only provide substrate-hosting biomimetic environments but also can integrate active sites in the confined nanospaces for function synergism. Herein, we demonstrate a vertex-directed organic-clip chelation assembly strategy to construct a metal-organic cage Fe4L68+ (MOC-63) incorporating 12 imidazole proton donor-acceptor motifs and four redox-active Fe centers in an octahedral coordination nanospace. Different from regular supramolecular cages assembled with coordination metal vertices, MOC-63 comprises six ditopic organic-clip ligands as vertices and four tris-chelating Fe(N∩N)3 moieties as faces, thus improving its acid, base, and redox robustness by virtue of cage-stabilized dynamics in solution. Improved dehydrogenation catalysis of 1,2,3,4-tetrahydroquinoline derivatives is accomplished by MOC-63 owing to a supramolecular cage effect that synergizes multiple Fe centers and radical species to expedite intermediate conversion of the multistep reactions in a cage-confined nanospace. The acid-base buffering imidazole motifs play a vital role in modulating the total charge state to resist pH variation and tune the solubility among varied solvents, thereby enhancing reaction acceleration in acidic conditions and rendering a facile recycling catalytic process.

Association between functional mitral regurgitation and recurrence of paroxysmal atrial fibrillation following catheter ablation: a prospective cohort study.

OBJECTIVE: The present study aimed to investigate the effect of functional mitral regurgitation (FMR) on recurrence of paroxysmal atrial fibrillation (PAF) in patients undergoing radiofrequency catheter ablation. METHODS: This prospective cohort study comprised 107 patients with PAF. The patients were divided into the FMR and non-FMR groups. FMR was assessed by Doppler echocardiography before index ablation. All patients initially underwent circumferential pulmonary vein isolation (CPVI) and were followed up for 12 months after ablation. PAF, atrial tachycardia, or atrial flutter served as the endpoint indicator. RESULTS: The median duration of PAF was 24 (3-60) months. Binary logistic univariate and multivariate analyses showed that FMR was not a risk factor for recurrence of catheter ablation for PAF (hazard ratio=0.758, 95% confidence interval: 0.191-3.004; hazard ratio=0.665, 95% confidence interval: 0.134-3.300, respectively). Kaplan-Meier analysis showed no significant difference in the recurrence rate between the groups. Fifteen (15/107, 14%) cases of PAF were triggered by the pulmonary vein. Three (3/107, 2.8%) cases of PAF were triggered by the superior vena cava. CONCLUSIONS: FMR is not an independent risk factor for predicting recurrence of catheter ablation for PAF. FMR does not affect patients undergoing radiofrequency catheter ablation for PAF.

Rh(III)-Catalyzed olefination to build diverse oxazole derivatives from functional alkynes.

A novel Rh(iii)-catalyzed olefination reaction of oxazoles to generate diverse oxazole skeleton derivatives has been realized by directly using oxazole as the directing group. The reaction could tolerate many functional groups, affording complex oxazole derivatives with long chain alkenyls in moderate to good yields, which might find applications in the construction of diverse compounds.

The association between platelet indices and cardiovascular events in chronic kidney disease patients without dialysis.

PURPOSE: Previous studies have indicated that platelet indices are related to the pathogenesis of cardiovascular diseases (CVD). However, it is unclear which platelet-related indicators are associated with CVD events in patients with chronic kidney disease (CKD) without dialysis. METHODS: We performed a single-center prospective cohort study involved 1391 CKD patients to explore the relationship between platelet indices and CVD events in CKD patients. A nomogram was generated to predict CVD-free survival after 3 and 5 years of follow-up in terms of the fitted Cox regression model. And the time-dependent receiver-operating characteristic (ROC) curves were applied to evaluate the prediction accuracy of platelet indices on CVD events. RESULTS: During a median follow-up of 3.41 years, 211 (15.2%) patients experienced CVD events. Results showed that platelet counts (PLT), plateletcrit (PCT), platelet-large cell ratio (P-LCR), and platelet distribution width (PDW) among 5 platelet indices were significantly lower in advanced CKD stages. Cox regression model showed that PLT, PDW, and PCT were associated with CVD events. However, after multivariable-adjusted, low level of PLT, hazard ratio (HR) 0.994 and 95% confidence interval (95% CI 0.989-1.000, p = 0.04), and PDW, HR 0.936 (95% CI 0.878-0.998, p = 0.044) predicted CVD events. The area under the ROC curve (AUC) of platelet indices assessed by time-dependent ROC curve analysis showed that only PLT and PDW were significant for predicting CVD events for 5 years. CONCLUSIONS: We demonstrated that PLT and PDW among 5 platelet indices were independently associated with CVD events in patients with CKD.

The high selective chemo-sensors for TNP based on the mono- and di-substituted multifarene[2,2] with different fluorescence quenching mechanism.

The chem-sensors, based on the triazole-CH2-anthracene-functionalized multifarene[2,2] were successfully synthesized, which could efficiently and rapidly detect 2,4,6-trinitrophenol (TNP). The high specificities of the proposed macrocyclic sensors were achieved by selective response for TNP in the existence of other competing phenolic compounds, and the limits of detection in ∼10-8 mol/L range were produced to confirm the high sensitivities of the chem-sensors, which could be attributed to the mechanism of electron and resonance energy transfer processes in the complexes with the supramolecular interactions. 1H NMR titration analysis revealed the actual binding position should be the triazole rings of sensors with the hydroxyl group on TNP to offer a hydrogen bonding. The extraordinary sensing properties endued the compounds as sensitive fluorometric chem-sensors for the potential application of TNP detection.

Spinal Cord Syphilitic Gumma Presenting with Brown-Séquard Syndrome: A Case Report and Literature Review.

BACKGROUND: Spinal neurosyphilis manifesting as a solitary syphilitic gumma is exceedingly rare. There are non-specific imaging findings and challenges in the diagnosis of spinal syphilitic gumma, which could be easily misdiagnosed as tumor lesions and require surgical resection or biopsy. CLINICAL PRESENTATION: We report the case of a 45-year-old female patient who was diagnosed with Spinal syphilitic gumma. Our case is the first reported case of spinal cord syphilitic gumma with intradural-extramedullary and intramedullary involvement. CONCLUSION: Spinal syphilitic gumma exhibits diverse clinical manifestations, lacks specific imaging features, accompanied by the patient's history deliberately concealed. Since clinicians do not have sufficient knowledge about such rare cases, misdiagnosis and missed diagnosis will be likely. When there is clinical suspicion for spinal syphilitic gumma, clinicians should pay close attention to relevant medical history, carry out a comprehensive physical examination and specific serological tests and cerebrospinal fluid (CSF) analysis. In summary, in cases with stable neurologic conditions, a trial administration of intravenous penicillin with follow-up imaging may be the optimal treatment option, and in cases with rapid progression or acute exacerbation, a surgical resection together with systemic antibiotic treatment for syphilis after surgery may be the best treatment strategy.

Recognition of silver cations by multifarene[2,2] chemosensors with unexpected fluorescence response.

Fluorescent chemosensors based on a new macrocyclic compound, multifarene[2,2], with modification by triazole-linked pyrene or anthracene were synthesized. These macrocyclic sensors exhibited high affinity and selectivity toward Ag+ over other metal ions, with ratiometric or enhanced response of their fluorescence emissions depending upon the substituent species for coordination to Ag+, and an unexpected response to a concentration threshold of the metal cations was discovered. The experimental evidences of fluorescence spectra, 1H NMR titration, IR spectra, and high-resolution mass spectra suggested the coordination behaviors of the sensors with Ag+, that is, the 1:1 complexes were formed with moderate association constants of about 105 L·mol-1, and the sulfur atoms on macrocyclic ligand should affinite to the metal cations. Energy-minimized structures and frontier orbitals were estimated by quantum chemical calculations with a view to rationalizing the fluorescence response of the multifarene[2,2] sensors upon binding to Ag+.

Association of uric acid with stenosis of intracranial and extracranial arteries in elderly patients with cerebral infarction.

BACKGROUND: To determine whether uric acid (UA) and intracranial and extracranial atherosclerosis stenosis of elderly patients suffering from ischaemic stroke are inter-related. METHODS: Elderly patients with ischaemic stroke underwent computed tomography angiography (CTA) were enrolled between October 2015 and December 2017. We collected clinical assessment, image data, and laboratory tests, and divided patients into four groups: (1) intracranial stenosis atherosclerosis (ICAS) group, (2) combined intracranial and extracranial atherosclerosis stenosis (COAS) group, (3) extracranial carotid stenosis atherosclerosis (ECAS) group, and (4) non-cerebral stenosis atherosclerosis (NCAS) group. We used univariate and multiple logistic regression analyses to explore potential predictors. RESULTS: We included 408 patients in this study, then divided them into elder group (n = 196) and young- and middle-aged group (n = 212). In old stroke patients, 72 cases (36.73%) were classified as the ICAS group, 45 cases (22.96%) as the COAS group, 21 cases (10.71%) as the ECAS group, and 58 cases (29.59%) as the NCAS group. The level of UA was comparatively higher (p = 0.033) in ICAS than in NCAS. Compared with the group which had only one stenosis artery, UA was substantially increased in patients with more than one stenosis intracranial artery (p < 0.001). With a multivariable analysis, UA was an independent predictor for intracranial stenosis of elderly patients (OR = 1.003, p = 0.042), but the relationship between extracranial artery stenosis and uric acid was negative. CONCLUSIONS: Hyperuricaemia is a risk factor of intracranial artery stenosis rather than of ECAS in elderly patients with cerebral infarction.

The impact of chronic intermittent hypoxia on the expression of intercellular cell adhesion molecule-1 and vascular endothelial growth factor in the ischemia-reperfusion rat model.

The aim of this study was to investigate the effect and mechanism of chronic intermittent hypoxia (CIH) on cerebral injury using the ischemia-reperfusion rat model. In total, 36 SD rats were divided into three groups: pseudo-surgery group (sham group), ischemia-reperfusion (IR) group (CIR group), and CIH intervention group (CIH group). The IR model was established using the suture-occluded method. CIH intervention was performed starting at 12 weeks prior to the establishment of the IR model for rats in the CIH group. Ultra-microstructure was examined using an electron microscope. Expression of intercellular cell adhesion molecule-1 (ICAM-1) and vascular endothelial growth factor (VEGF) in rat brain tissue was evaluated by immunohistochemical methods and western blot assays. The neurological deficit scores of rats in the CIH group were higher than those in the CIR group (p < 0.05). Using electron microscopy, we observed more severe edema around the capillaries of the rat brain that resulted in more pressure on the vascular wall of the capillaries in the CIH group compared to the CIR group. The expression of ICAM-1 and VEGF in rat brain tissue was rare in the sham group, but was significantly elevated in the CIR group (p < 0.05) and even higher in the CIH group, compared to the CIR group. Hence, the brain injury in ischemia-reperfusion rat models following CIH intervention may be related to the increased expression of ICAM-1 and VEGF.