Integrative Approaches in Acute Ischemic Stroke: From Symptom Recognition to Future Innovations

Stem cell grafts enhance endogenous extracellular vesicle expression in the stroke brain

Endogenous brain repair occurs following an ischemic stroke but is transient, thus unable to fully mount a neuroprotective response against the evolving secondary cell death. Finding a treatment strategy that may render robust and long-lasting therapeutic effects stands as a clinically relevant therapy for stroke. Extracellular vesicles appear to be upregulated after stroke, which may represent a candidate target for neuroprotection. In this study, we probed whether transplanted stem cells could enhance the expression of extracellular vesicles to afford stable tissue remodeling in the ischemic stroke brain. Aged rats were initially exposed to the established ischemic stroke model of middle cerebral artery occlusion then received intravenous delivery of either bone marrow-derived mesenchymal stem cell transplantation or vehicle. A year later, the animals were assayed for brain damage, inflammation, and extracellular vesicle expression. Our findings revealed that while core infarction was not reduced, the stroke animals transplanted with stem cells displayed a significant reduction in peri-infarct cell loss that coincided with downregulated Iba1-labeled inflammatory cells and upregulated CD63-positive extracellular vesicles that appeared to be co-localized with GFAP-positive astrocytes. Interestingly, grafted stem cells were not detected at one year post-transplantation period, suggesting that the extracellular vesicles likely originated within the host brain. That long-lasting functional benefits persisted in the absence of surviving transplanted stem cells, but with upregulation of endogenous extracellular vesicles, advances the concept that transplantation of stem cells acutely after stroke propels host extracellular vesicles to the ischemic brain, altogether promoting chronic brain remodeling.

Proteomics profiling of extracellular vesicle for identification of potential biomarkers in Alzheimer's disease: A comprehensive review

The intricate origins and diverse symptoms of Alzheimer's disease (AD) pose significant challenges for both diagnosis and treatment. Exosomes and microvesicles, which carry disease-specific cargo from a variety of central nervous system cell types, have emerged as promising reservoirs of biomarkers for AD. Research on the screening of possible biomarkers in Alzheimer's disease using proteomic profiling of EVs is systematically reviewed in this comprehensive review. We highlight key methodologies employed in EV isolation, characterization, and proteomic analysis, elucidating their advantages and limitations. Furthermore, we summarize the evolving landscape of EV-associated biomarkers implicated in AD pathogenesis, including proteins involved in amyloid-beta metabolism, tau phosphorylation, neuroinflammation, synaptic dysfunction, and neuronal injury. The literature review highlights the necessity for robust validation strategies and standardized protocols to effectively transition EV-based biomarkers into clinical use. In the concluding section, this review delves into potential future avenues and technological advancements pivotal in crafting EV-derived biomarkers applicable to AD diagnostics and prognostics. This review contributes to our comprehension of AD pathology and the advancement of precision medicine in neurodegenerative diseases, hinting at a promising era in AD precision medicine.

A Decade of Dedication: Pioneering Perspectives on Neurological Diseases and Mental Illnesses

Welcome to Biomedicines' 10th Anniversary Special Issue, a journey through the human mind's labyrinth and complex neurological pathways [...].

The Role of Artificial Intelligence-Powered Imaging in Cerebrovascular Accident Detection

Cerebrovascular accidents (CVAs) often occur suddenly and abruptly, leaving patients with long-lasting disabilities that place a huge emotional and economic burden on everyone involved. CVAs result when emboli or thrombi travel to the brain and impede blood flow; the subsequent lack of oxygen supply leads to ischemia and eventually tissue infarction. The most important factor determining the prognosis of CVA patients is time, specifically the time from the onset of disease to treatment. Artificial intelligence (AI)-assisted neuroimaging alleviates the time constraints of analysis faced using traditional diagnostic imaging modalities, thus shortening the time from diagnosis to treatment. Numerous recent studies support the increased accuracy and processing capabilities of AI-assisted imaging modalities. However, the learning curve is steep, and huge barriers still exist preventing a full-scale implementation of this technology. Thus, the potential for AI to revolutionize medicine and healthcare delivery demands attention. This paper aims to elucidate the progress of AI-powered imaging in CVA diagnosis while considering traditional imaging techniques and suggesting methods to overcome adoption barriers in the hope that AI-assisted neuroimaging will be considered normal practice in the near future. There are multiple modalities for AI neuroimaging, all of which require collecting sufficient data to establish inclusive, accurate, and uniform detection platforms. Future efforts must focus on developing methods for data harmonization and standardization. Furthermore, transparency in the explainability of these technologies needs to be established to facilitate trust between physicians and AI-powered technology. This necessitates considerable resources, both financial and expertise wise which are not available everywhere.

Elevated troponin levels as a predictor of mortality in patients with acute stroke: a systematic review and meta-analysis

Background and Aim

The prognostic potential of cardiac troponin (cTn) in acute stroke patients has been a subject of ongoing debate. Our objective was to provide a comprehensive evidence for predicting mortality in acute stroke patients by using the elevated troponin levels.

Methods

We conducted an extensive literature search, including PubMed, EMbase, and Trip Databases, covering studies published up to September 30, 2023. We computed risk ratios (RR) with 95% confidence intervals (CIs), performed sensitivity analysis, and conducted trial sequential analysis (TSA).

Results

In total, 53 studies were analyzed, with 37 focusing on acute ischemic stroke (AIS), 11 on subarachnoid hemorrhage (SAH), and 7 on Intracerebral hemorrhage (ICH). Elevated cTn levels were significantly showed a higher predictive risk for In-hospital mortality in both AIS (RR=3.80, 95% CI; 2.82 to 5.12) as well as SAH (RR=2.23, 95% CI; 1.64 to 3.02). However, no significant predictive risk between elevated cTn levels and in-hospital mortality for ICH patients (RR=1.13, 95% CI: 0.46 to 2.79). A similar pattern was observed for elevated cTn levels, indicating an increased risk of last follow-up mortality for AIS (RR=2.41, 95% CI: 1.98 to 2.93) and SAH (RR=3.08, 95% CI: 2.25 to 4.21).

Conclusion

Elevated troponin levels can serve as a promising predictive marker for both in-hospital and last follow-up mortality in AIS and SAH patients but not in ICH patients. Further prospective studies are needed to validate our findings along with exploring the preventive management of mortality in acute stroke settings.

Correlation Between Oncostatin M and Acute Ischemic Stroke: A Case-Control Study

BACKGROUND

The expression of oncostatin M (OSM) has been studied in various diseases related to inflammatory response, but its implementation in acute ischemic stroke (AIS) remains to be explored.  Objective: The objective of this study is to assess the correlation between serum OSM expression and various aspects of AIS in a clinical setting.

MATERIALS AND METHOD

A single-centered case-control study was performed in the First Affiliate Hospital of Chongqing Medical University from October 2020 to March 2021. A total of 134 patients were enrolled in the AIS group and 34 healthy individuals were enrolled in the control group. Physical examinations were performed and venous blood samples were collected. Enzyme-linked immunosorbent assay (ELISA) was used to measure serum OSM. Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification, National Institutes of Health Stroke Scale (NIHSS) score, magnetic resonance imaging (MRI) scan, and modified Rankin scale (mRS) were used to assess the classification, etiology, severity, and prognosis of the AIS group. Assessments were done to analyze serum OSM expression based on sensitivity, etiology, severity, prognosis, and several risk factors of AIS. Regression models, correlation, and sensitivity tests were performed to explore the correlation of OSM expression with various aspects of AIS.

RESULTS

There was a statistically significant elevation of serum OSM expression in the AIS group (P<0.001). All AIS subgroups showed elevation in OSM level and statistically significant results were reflected in three subgroups. The area under the curve to differentiate AIS patients and control by serum OSM level was 0.747 (P<0.001), with the optimal cut-off value showing sensitivity at 58.82% and specificity at 75.37%. The elevation of serum OSM expression was proportional with severity, not proportional to the volume of infarct, and less elevated in the favorable outcome group. Serum OSM correlation with several risk factors of AIS was statistically significant in age, low-density lipoprotein, non-high-density lipoprotein, prothrombin time, and systolic blood pressure.

CONCLUSION

Serum OSM was expressed differently in correlation with various aspects of AIS. Our findings supported the initial hypothesis that OSM is correlated with various aspects of AIS in humans.