Carotid artery transplantation of brain endothelial cells enhances neuroprotection and neurorepair in ischaemic stroke rats.

Brain microvascular endothelial cells (BMECs), an important component of the neurovascular unit, can promote angiogenesis and synaptic formation in ischaemic mice after brain parenchyma transplantation. Since the therapeutic efficacy of cell-based therapies depends on the extent of transplanted cell residence in the target tissue and cell migration ability, the delivery route has become a hot research topic. In this study, we investigated the effects of carotid artery transplantation of BMECs on neuronal injury, neurorepair, and neurological dysfunction in rats after cerebral ischaemic attack. Purified passage 1 endothelial cells (P1-BMECs) were prepared from mouse brain tissue. Adult rats were subjected to transient middle cerebral artery occlusion (MCAO) for 30 min. Then, the rats were treated with 5 × 105 P1-BMECs through carotid artery infusion or tail vein injection. We observed that carotid artery transplantation of BMECs produced more potent neuroprotective effects than caudal injection in MCAO rats, including reducing infarct size and alleviating neurological deficits in behavioural tests. Carotid artery-transplanted BMECs displayed a wider distribution in the ischaemic rat brain. Immunostaining for endothelial progenitor cells and the mature endothelial cell markers CD34 and RECA-1 showed that carotid artery transplantation of BMECs significantly increased angiogenesis. Carotid artery transplantation of BMECs significantly increased the number of surviving neurons, decreased the cerebral infarction volume, and alleviated neurological deficits. In addition, we found that carotid artery transplantation of BMECs significantly enhanced ischaemia-induced hippocampal neurogenesis, as measured by doublecortin (DCX) and Ki67 double staining within 2 weeks after ischaemic injury. We conclude that carotid artery transplantation of BMECs can promote cerebral angiogenesis, neurogenesis, and neurological function recovery in adult rats after ischaemic stroke. Our results suggest that carotid injection of BMECs may be a promising new approach for treating acute brain injuries.

NMR based Serum metabolomics revealed metabolic signatures associated with oxidative stress and mitochondrial damage in brain stroke.

Brain stroke (BS, also known as a cerebrovascular accident), represents a serious global health crisis. It has been a leading cause of permanent disability and unfortunately, frequent fatalities due to lack of timely medical intervention. While progress has been made in prevention and management, the complexities and consequences of stroke continue to pose significant challenges, especially, its impact on patient's quality of life and independence. During stroke, there is a substantial decrease in oxygen supply to the brain leading to alteration of cellular metabolic pathways, including those involved in mitochondrial-damage, leading to mitochondrial-dysfunction. The present proof-of-the-concept metabolomics study has been performed to gain insights into the metabolic pathways altered following a brain stroke and discover new potential targets for timely interventions to mitigate the effects of cellular and mitochondrial damage in BS. The serum metabolic profiles of 108 BS-patients were measured using 800 MHz NMR spectroscopy and compared with 60 age and sex matched normal control (NC) subjects. Compared to NC, the serum levels of glutamate, TCA-cycle intermediates (such as citrate, succinate, etc.), and membrane metabolites (betaine, choline, etc.) were found to be decreased BS patients, whereas those of methionine, mannose, mannitol, phenylalanine, urea, creatine and organic acids (such as 3-hydroxybutyrate and acetone) were found to be elevated in BS patients. These metabolic changes hinted towards hypoxia mediated mitochondrial dysfunction in BS-patients. Further, the area under receiver operating characteristic curve (ROC) values for five metabolic features (methionine, mannitol, phenylalanine, mannose and urea) found to be more than 0.9 suggesting their high sensitivity and specificity for differentiating BS from NC subjects.

Comprehensive Review: Machine and Deep Learning in Brain Stroke Diagnosis.

Brain stroke, or a cerebrovascular accident, is a devastating medical condition that disrupts the blood supply to the brain, depriving it of oxygen and nutrients. Each year, according to the World Health Organization, 15 million people worldwide experience a stroke. This results in approximately 5 million deaths and another 5 million individuals suffering permanent disabilities. The complex interplay of various risk factors highlights the urgent need for sophisticated analytical methods to more accurately predict stroke risks and manage their outcomes. Machine learning and deep learning technologies offer promising solutions by analyzing extensive datasets including patient demographics, health records, and lifestyle choices to uncover patterns and predictors not easily discernible by humans. These technologies enable advanced data processing, analysis, and fusion techniques for a comprehensive health assessment. We conducted a comprehensive review of 25 review papers published between 2020 and 2024 on machine learning and deep learning applications in brain stroke diagnosis, focusing on classification, segmentation, and object detection. Furthermore, all these reviews explore the performance evaluation and validation of advanced sensor systems in these areas, enhancing predictive health monitoring and personalized care recommendations. Moreover, we also provide a collection of the most relevant datasets used in brain stroke analysis. The selection of the papers was conducted according to PRISMA guidelines. Furthermore, this review critically examines each domain, identifies current challenges, and proposes future research directions, emphasizing the potential of AI methods in transforming health monitoring and patient care.

An Update of Kaempferol Protection against Brain Damage Induced by Ischemia-Reperfusion and by 3-Nitropropionic Acid.

Kaempferol, a flavonoid present in many food products, has chemical and cellular antioxidant properties that are beneficial for protection against the oxidative stress caused by reactive oxygen and nitrogen species. Kaempferol administration to model experimental animals can provide extensive protection against brain damage of the striatum and proximal cortical areas induced by transient brain cerebral ischemic stroke and by 3-nitropropionic acid. This article is an updated review of the molecular and cellular mechanisms of protection by kaempferol administration against brain damage induced by these insults, integrated with an overview of the contributions of the work performed in our laboratories during the past years. Kaempferol administration at doses that prevent neurological dysfunctions inhibit the critical molecular events that underlie the initial and delayed brain damage induced by ischemic stroke and by 3-nitropropionic acid. It is highlighted that the protection afforded by kaempferol against the initial mitochondrial dysfunction can largely account for its protection against the reported delayed spreading of brain damage, which can develop from many hours to several days. This allows us to conclude that kaempferol administration can be beneficial not only in preventive treatments, but also in post-insult therapeutic treatments.

Analysis of the Intensity of Nitric Oxide Production in Different Parts of the Spinal Cord after Modeling Combined Cerebral and Spinal Injury.

Using the method of electron paramagnetic resonance spectroscopy, we showed that NO production decreases by 60% (p<0.05) in the region located rostral to the spinal cord injury 7 days after combined injury to the brain and spinal cord. At the same time, NO production did not change in the site of spinal cord injury and caudal to the injury. The intensity of NO production in similar parts of the spinal cord in intact animals remained unchanged.

A search for acrolein scavengers among food components.

Brain stroke is a major cause of being bedridden for elderly people, and preventing stroke is important for maintaining quality of life (QOL). Acrolein is a highly reactive aldehyde and causes tissue damage during stroke. Decreasing acrolein toxicity ameliorates tissue injury during brain stroke. In this study, we tried to identify food components which decrease acrolein toxicity. We found that 2-furanmethanethiol, cysteine methyl and ethyl esters, alliin, lysine and taurine decreased acrolein toxicity. These compounds neutralized acrolein by direct interaction. However, the interaction between acrolein and taurine was not so strong. Approximately 30 mM taurine was necessary to interact with 10 µM acrolein, and 2 g/kg taurine was necessary to decrease the size of mouse brain infarction. Taurine also slightly increased polyamine contents, which are involved in decrease in the acrolein toxicity. Mitochondrial potential damage by acrolein was also protected by taurine. Our results indicate that daily intake of foods containing 2-furanmethanethiol, cysteine methyl and ethyl esters, alliin, lysine and taurine may prevent severe injury in brain stroke and improve the quality of life for elderly people.

Capsaicin, The Vanilloid Receptor TRPV1 Agonist in Neuroprotection: Mechanisms Involved and Significance.

Hot peppers, also called chilli, chilli pepper, or paprika of the plant genus Capsicum (family Solanaceae), are one of the most used vegetables and spices worldwide. Capsaicin (8-methyl N-vanillyl-6-noneamide) is the main pungent principle of hot green and red peppers. By acting on the capsaicin receptor or transient receptor potential cation channel vanilloid subfamily member 1 (TRPV1), capsaicin selectively stimulates and in high doses defunctionalizes capsaicin-sensitive chemonociceptors with C and Aδ afferent fibers. This channel, which is involved in a wide range of neuronal processes, is expressed in peripheral and central branches of capsaicin-sensitive nociceptive neurons, sensory ganglia, the spinal cord, and different brain regions in neuronal cell bodies, dendrites, astrocytes, and pericytes. Several experimental and clinical studies provided evidence that capsaicin protected against ischaemic or excitotoxic cerebral neuronal injury and may lower the risk of cerebral stroke. By preventing neuronal death, memory impairment and inhibiting the amyloidogenic process, capsaicin may also be beneficial in neurodegenerative disorders such as Parkinson's or Alzheimer's diseases. Capsaicin given in systemic inflammation/sepsis exerted beneficial antioxidant and anti-inflammatory effects while defunctionalization of capsaicin-sensitive vagal afferents has been demonstrated to increase brain oxidative stress. Capsaicin may act in the periphery via the vagal sensory fibers expressing TRPV1 receptors to reduce immune oxidative and inflammatory signalling to the brain. Capsaicin given in small doses has also been reported to inhibit the experimentally-induced epileptic seizures. The aim of this review is to provide a concise account on the most recent findings related to this topic. We attempted to delineate such mechanisms by which capsaicin exerts its neuronal protective effects. We also aimed to provide the reader with the current knowledge on the mechanism of action of capsaicin on sensory receptors.

On the Role of Training Data for SVM-Based Microwave Brain Stroke Detection and Classification.

The aim of this work was to test microwave brain stroke detection and classification using support vector machines (SVMs). We tested how the nature and variability of training data and system parameters impact the achieved classification accuracy. Using experimentally verified numerical models, a large database of synthetic training and test data was created. The models consist of an antenna array surrounding reconfigurable geometrically and dielectrically realistic human head phantoms with virtually inserted strokes of arbitrary size, and different dielectric parameters in different positions. The generated synthetic data sets were used to test four different hypotheses, regarding the appropriate parameters of the training dataset, the appropriate frequency range and the number of frequency points, as well as the level of subject variability to reach the highest SVM classification accuracy. The results indicate that the SVM algorithm is able to detect the presence of the stroke and classify it (i.e., ischemic or hemorrhagic) even when trained with single-frequency data. Moreover, it is shown that data of subjects with smaller strokes appear to be the most suitable for training accurate SVM predictors with high generalization capabilities. Finally, the datasets created for this study are made available to the community for testing and developing their own algorithms.

Investigation of NO Role in Neural Tissue in Brain and Spinal Cord Injury.

Nitric oxide (NO) production in injured and intact brain regions was compared by EPR spectroscopy in a model of brain and spinal cord injury in Wistar rats. The precentral gyrus of the brain was injured, followed by the spinal cord at the level of the first lumbar vertebra. Seven days after brain injury, a reduction in NO content of 84% in injured brain regions and 66% in intact brain regions was found. The difference in NO production in injured and uninjured brain regions persisted 7 days after injury. The copper content in the brain remained unchanged one week after modeling of brain and spinal cord injury. The data obtained in the experiments help to explain the problems in the therapy of patients with combined brain injury.

Activation of BDNF- and VEGF-mediated Neuroprotection by Treadmill Exercise Training in Experimental Stroke.

Early treatment of ischemic stroke is one of the most effective ways to reduce brains' cell death and promote functional recovery. This study was designed to examine the effect of aerobic exercise on post ischemia/reperfusion injury on concentration and expression of brain-derived neurotrophic factor (BDNF) and vascular endothelial growth factor (VEGF) after inducing a neuronal loss in CA1 region of hippocampus in Male Wistar rats. Three experimental groups including sham(S), ischemia/reperfusion-control (IRC) and ischemia/reperfusion exercise (IRE) were used for this purpose. The rats in the IRE group received a bilateral carotid artery occlusion treatment. They ran for 45 minutes on a treadmill five days per week for eight consecutive weeks. Cresyl violet (Nissl), Hematoxylin (H & E) and Eosin staining procedure were used to determine the extent of damage. A ladder rung walking task was used to assess the functional impairments and recovery after the ischemic lesion. ELISA and immunohistochemistry method were employed to measure BDNF and VEGF protein expressions. The result showed that the brain ischemia/reperfusion condition increased the cell death in hippocampal CA1 neurons and impaired motor performance on the ladder rung task whereas the aerobic exercise program significantly decreased the brain cell's death and improved motor skill performance. It was concluded that ischemic brain lesion decreased the BDNF and VEGF expression. It seems that the aerobic exercise following the ischemia/reperfusion potentially promotes neuroprotective mechanisms and neuronal repair and survival mediated partly by BDNF and other pathways.

Radioimaging and Demographic Profiles of Patients with Spontaneous Intracerebral Hemorrhage: A Need for the Pragmatic Referral System.

Referring patients with severe medical conditions, like brain stroke, from small or rural hospitals to tertiary care centers is often overexploited leading to a kind of defensive medicine. The issue of a patient referral system remains unaddressed in Nepal. In this article, we investigated the legitimacy of referring patients with spontaneous intracranial hemorrhage (ICH) from country peripheral hospitals to the leading tertiary neurological center in Nepal. We found that 81 out of the 130 ICH patients reviewed in the study were referred. We further show that the classifiers to be considered most in the decision-making on the patient referral are as follows: hematoma volume, midline shift found in radioimaging, ventricular extension of bleeding, and appearance of hydrocephalus. An improper referral of the patient to the tertiary care center decreases limited resources of healthcare services in low-income countries. We believe the study reflects a prevailing belief among healthcare professionals that the current referral system could be improved with the inception of the "hub and spoke" model of healthcare. In this model, a network of secondary health institutions, capable of offering limited treatment, would refer ICH patients to an anchor tertiary institution, respecting the proper dichotomization of patients based on the clinical classifiers. We conclude that the use of the "hub and spoke" model, legitimizing the patient referral system, is posed to offer medical benefits for patients hit by a stroke and would be economically viable for both patients and healthcare services.

A Novel Discretization Procedure in the CSI-FEM Algorithm for Brain Stroke Microwave Imaging.

In this work, the contrast source inversion method is combined with a finite element method to solve microwave imaging problems. The paper's major contribution is the development of a novel contrast source variable discretization that leads to simplify the algorithm implementation and, at the same time, to improve the accuracy of the discretized quantities. Moreover, the imaging problem is recreated in a synthetic environment, where the antennas, and their corresponding coaxial port, are modeled. The implemented algorithm is applied to reconstruct the tissues' dielectric properties inside the head for brain stroke microwave imaging. The proposed implementation is compared with the standard one to evaluate the impact of the variables' discretization on the algorithm's accuracy. Furthermore, the paper shows the obtained performances with the proposed and the standard implementations of the contrast source inversion method in the same realistic 3D scenario. The exploited numerical example shows that the proposed discretization can reach a better focus on the stroke region in comparison with the standard one. However, the variation is within a limited range of permittivity values, which is reflected in similar averages.

Neutrophil-targeted engineered prodrug nanoparticles for anti-inflammation.

Inflammation response is a defense to infection induced by invading pathogen or tissue injury. However, exaggerated inflammation may cause autoimmune or inflammatory disorders, such as acute respiratory distress syndrome, sepsis, stroke and rheumatoid arthritis. Anti-inflammatory agents and anti-cytokine therapy have been developed to inhibit inflammation pathways and neutralize cytokine storm, but the off-targeting delivery and damage in immune system cause systemic severe side-effect. Selective targeting, precise intracellular drug delivery and induced programed apoptosis of neutrophils may be a potential strategy to regulate the inflammatory responses for immune homeostasis. In this commentary, we summarized that the assembled engineering prodrug nanoparticles carrying doxorubicin via pH-responsive bonds that specifically target to and efficiently induce the apoptosis of activated neutrophils for anti-inflammation with high therapeutic efficacy and no systemically toxicity could be a promising strategy for neutrophil-mediated diseases.

The effect of PCSK9 inhibitors on brain stroke prevention: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Although proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors have been shown to improve cardiovascular outcomes, their effects on brain stroke risk are unclear. The present meta-analysis aimed to evaluate the effects of PCSK9 inhibitors on brain stroke prevention. METHODS AND RESULTS: We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov for research published until December 30, 2020, to find randomized controlled trials (RCTs) of PCSK9 inhibitors for brain stroke prevention. Relative risk (RR) and 95% confidence intervals (CIs) were used to represent the outcomes. Seven RCTs with 57,440 participants, including 29,850 patients treated with PCSK9 inhibitors and 27,590 control participants, were included. PCSK9 inhibitors were associated with significant reductions in total brain stroke risk (RR, 0.77; 95% CI, 0.67-0.88; P < 0.001) and ischemic brain stroke risk (RR, 0.76; 95% CI, 0.66, 0.89; P < 0.001) in comparison with the control group. There was no significant difference in cardiovascular mortality (RR, 0.95; 95% CI, 0.84-1.07; P = 0.382) and the risk of hemorrhagic brain stroke (RR, 1.00; 95% CI, 0.66-1.51; P = 0.999) between patients treated with PCSK9 inhibitors and controls. PCSK9 inhibitors did not significantly increase the incidence of neurocognitive adverse events (RR, 1.02; 95% CI, 0.81-1.29; P = 0.85). Moreover, subgroup analysis showed no difference in cognitive function disorder risks among different PCSK9 inhibitors and treatment times. CONCLUSIONS: PCSK9 inhibitors significantly reduced the risk of total brain stroke and ischemic brain stroke without increasing the risk of brain hemorrhage and neurocognitive impairment.

A Review on Computer Aided Diagnosis of Acute Brain Stroke.

Amongst the most common causes of death globally, stroke is one of top three affecting over 100 million people worldwide annually. There are two classes of stroke, namely ischemic stroke (due to impairment of blood supply, accounting for ~70% of all strokes) and hemorrhagic stroke (due to bleeding), both of which can result, if untreated, in permanently damaged brain tissue. The discovery that the affected brain tissue (i.e., 'ischemic penumbra') can be salvaged from permanent damage and the bourgeoning growth in computer aided diagnosis has led to major advances in stroke management. Abiding to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines, we have surveyed a total of 177 research papers published between 2010 and 2021 to highlight the current status and challenges faced by computer aided diagnosis (CAD), machine learning (ML) and deep learning (DL) based techniques for CT and MRI as prime modalities for stroke detection and lesion region segmentation. This work concludes by showcasing the current requirement of this domain, the preferred modality, and prospective research areas.

A Prototype Microwave System for 3D Brain Stroke Imaging.

This work focuses on brain stroke imaging via microwave technology. In particular, the open issue of monitoring patients after stroke onset is addressed here in order to provide clinicians with a tool to control the effectiveness of administered therapies during the follow-up period. In this paper, a novel prototype is presented and characterized. The device is based on a low-complexity architecture which makes use of a minimum number of properly positioned and designed antennas placed on a helmet. It exploits a differential imaging approach and provides 3D images of the stroke. Preliminary experiments involving a 3D phantom filled with brain tissue-mimicking liquid confirm the potential of the technology in imaging a spherical target mimicking a stroke of a radius equal to 1.25 cm.

Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection.

In this paper, we present an investigation of different artefact removal methods for ultra-wideband Microwave Imaging (MWI) to evaluate and quantify current methods in a real environment through measurements using an MWI device. The MWI device measures the scattered signals in a multi-bistatic fashion and employs an imaging procedure based on Huygens principle. A simple two-layered phantom mimicking human head tissue is realised, applying a cylindrically shaped inclusion to emulate brain haemorrhage. Detection has been successfully achieved using the superimposition of five transmitter triplet positions, after applying different artefact removal methods, with the inclusion positioned at 0°, 90°, 180°, and 270°. The different artifact removal methods have been proposed for comparison to improve the stroke detection process. To provide a valid comparison between these methods, image quantification metrics are presented. An "ideal/reference" image is used to compare the artefact removal methods. Moreover, the quantification of artefact removal procedures through measurements using MWI device is performed.

Stroke Mimics: Experience of a Moroccan Stroke Unit.

BACKGROUND: Stroke mimic is a medical condition presenting with acute neurological deficit and simulate real stroke. The objective of this study was to evaluate the frequency and the various etiologies of stroke mimics in our center. METHODS: We retrospectively reviewed the Thrombolysis Alert registry and we studied the frequency and characteristics of patients with stroke mimic. RESULTS: Among 673 patients who were admitted to the emergency department within 4.5 hours for sudden focal neurological deficit suggestive of acute stroke, 105 patients (15.6 %) had a stroke mimic. The mean age of patients with mimics and brain strokes were 66.3 and 64.8, respectively. The mean Onset-to-door time was 136.82 minutes and the mean door-to-imaging time was 32.63 minutes in stroke mimics. Seizure (28.5%) was the most common diagnosis of stroke mimics followed by conversion disorder (25.7%). CONCLUSIONS: Stroke mimic is frequent and heterogeneous entity that can be difficult to identify. Fortunately, most previous studies show no harmful effects when using thrombolysis in a stroke mimic.

[Diversified Innovation Strategies for an Early Limb Rehabilitation Program in Patients With Stroke].

BACKGROUND & PROBLEMS: Early rehabilitation after stroke is important for the recovery of bodily functions in stroke patients. However, the percentage of completion of early limb rehabilitation among stroke patients is only 16%. PURPOSE: Raise the early rehabilitation intervention rate to 88% for patients with stroke within 24 hours of hospitalization. RESOLUTION: We developed an education course on post-stroke rehabilitation and a related e-Learning course as well as organized an 'alliance for recovery' team. In addition, we established a standard for post-stroke relay rehabilitation and designed rehabilitation relay cards, Xbox rehabilitation games, and nine squares challenge for brain stroke care. RESULTS: The accuracy of the knowledge of nursing staff related to physical rehabilitation improved from 72.4% to 100%; the accuracy of their perceptions regarding early limb rehabilitation increased from 16% to 100%; and patient satisfaction increased from 68% to 98%. CONCLUSIONS: We deployed diverse and innovative strategies to assist limb rehabilitation in patients with stroke. Patients and caregivers should be encouraged to participate in early rehabilitation and related programs and should apply the skills and rehabilitation activities learned to daily life.

The outcome in patients with brain stroke: A deep learning neural network modeling.

BACKGROUND: The artificial intelligence field is obtaining ever-increasing interests for enhancing the accuracy of diagnosis and the quality of patient care. Deep learning neural network (DLNN) approach was considered in patients with brain stroke (BS) to predict and classify the outcome by the risk factors. MATERIALS AND METHODS: A total of 332 patients with BS (mean age: 77.4 [standard deviation: 10.4] years, 50.6% - male) from Imam Khomeini Hospital, Ardabil, Iran, during 2008-2018 participated in this prospective study. Data were gathered from the available documents of the BS registry. Furthermore, the diagnosis of BS was considered based on computerized tomography scans and magnetic resonance imaging. The DLNN strategy was applied to predict the effects of the main risk factors on mortality. The quality of the model was measured by diagnostic indices. RESULTS: The finding of this study for 81 selected models demonstrated that ranges of accuracy, sensitivity, and specificity are 90.5%-99.7%, 83.8%-100%, and 89.8%-99.5%, respectively. Based on the optimal model (tangent hyperbolic activation function with the minimum-maximum hidden units of 10-20, max epochs of 400, momentum of 0.5, and learning rate of 0.1), the most important predictors for BS mortality were time interval after 10 years (accuracy = 92.2%), age category (75.6%), the history of hyperlipoproteinemia (66.9%), and education level (66.9%). The other independent variables are at moderate importance (66.6%) which include sex, employment status, residential place, smoking habits, history of heart disease, cerebrovascular accident type, blood pressure, diabetes, oral contraceptive pill use, and physical activity. CONCLUSION: The best means for dropping the BS load is effective BS prevention. DLNN strategy showed a surprising presentation in the prediction of BS mortality based on the main risk factors with an excellent diagnostic accuracy. Moreover, the time interval after 10 years, age, the history of hyperlipoproteinemia, and education level are the most important predictors for BS.