Ferroptosis plays a critical role in ischemic stroke, and anti-ferroptosis strategies were regarded as potentially effective measures. Based on ferroptosis-related mechanisms, this study aims to design and prepare anti-ferroptosis exosomes from adipose-derived mesenchymal stem cells (ADSC-Exo) for treating ischemic brain injury via intranasal (IN) administration. According to the bioinformatic analysis, CHAC1 was a key gene in the progress of ferroptosis in ischemic stroke. miR-760-3p can inhibit the expression of CHAC1 and may be abundant in ADSC-Exo. Therefore, ADSC-Exo were successfully isolated and the immunofluorescence showed that they can be efficiently delivered to the brain via IN administration. Additionally, IN administration of ADSC-Exo can effectively improve the neurobehavior function of mice after I/R, and improve the ferroptosis-related outcomes. As the immunofluorescence showed the co-localization of NeuN with CHAC1 obviously, we further evaluated the systematic effect of ADSC-Exo in an oxygen–glucose deprivation (OGD) mouse neuroblastoma cell line N2a model. The results showed that miR-760-3p in ADSC‐Exo contributed to their function in inhibiting ferroptosis by targeting CHAC1 in neurons. Collectively, the present study successfully designed and prepared anti-CHAC1 ADSC-Exo and suggested a promising exosome-based strategy for anti-ferroptosis therapy in cerebral ischemia/reperfusion injury. Graphical abstract

Background: Stroke is a devastating disease affecting populations worldwide and is the primary cause of long-term disability. The inflammatory storm plays a crucial role in the progression of stroke. In the acute phase of ischemic stroke, there is a transient increase in anti-inflammatory M2 microglia followed by a rapid decline. Due to the abundant phospholipid in brain tissue, lipid peroxidation is a notable characteristic of ischemia/reperfusion (I/R), constituting a structural foundation for ferroptosis in M2 microglia. Slowing down the decrease in M2 microglia numbers and controlling the inflammatory microenvironment holds significant potential for enhancing stroke recovery. Results: We found that the ferroptosis inhibitor can modulate inflammatory response in MCAO mice, characterizing that the level of M2 microglia-related cytokines was increased. We then confirmed that different subtypes of microglia exhibit distinct sensitivities to I/R-induced ferroptosis. Adipose-derived stem cells derived exosome (ADSC-Exo) effectively decreased the susceptibility of M2 microglia to ferroptosis via Fxr2/Atf3/Slc7a11, suppressing the inflammatory microenvironment and promoting neuronal survival. Furthermore, through plasmid engineering, a more efficient M2 microglia-targeted exosome, termed M2pep-ADSC-Exo, was developed. In vivo and in vitro experiments demonstrated that M2pep-ADSC-Exo exhibits significant targeting specificity for M2 microglia, further inhibiting M2 microglia ferroptosis and improving neurological function in ischemic stroke mice. Conclusion: Collectively, we illustrated a novel potential therapeutic mechanism that Fxr2 in ADSC-Exo could alleviate the M2 microglia ferroptosis via regulating Atf3/Slc7all expression, hence inhibiting the inflammatory microenvironment, improving neurofunction recovery in cerebral I/R injury. We obtained a novel exosome, M2pep-ADSC-Exo, through engineered modification, which exhibits improved targeting capabilities toward M2 microglia. This provides a new avenue for the treatment of stroke. Graphical

Background. Ischemic stroke is a severe acute cerebrovascular disease which can be improved with neuroprotective therapies at an early stage. However, due to the lack of effective neuroprotective drugs, most stroke patients have varying degrees of long-term disability. In the present study, we investigated the role of exosomes derived from CXCR4-overexpressing BMSCs in restoring vascular function and neural repair after ischemic cerebral infarction. Methods. BMSCs were transfected with lentivirus encoded by CXCR4 (BMSC^CXCR4). Exosomes derived from BMSC^CXCR4 (Exo^CXCR4) were isolated and characterized by transmission electron microscopy and dynamic light scattering. Western blot and qPCR were used to analyze the expression of CXCR4 in BMSCs and exosomes. The acute middle cerebral artery occlusion (MCAO) model was prepared, Exo^CXCR4 were injected into the rats, and behavioral changes were analyzed. The role of Exo^CXCR4 in promoting the proliferation and tube formation for angiogenesis and protecting brain endothelial cells was determined in vitro. Results. Compared with the control groups, the Exo^CXCR4 group showed a significantly lower mNSS score at 7 d, 14 d, and 21 d after ischemia/reperfusion ( ). The bEnd.3 cells in the Exo^CXCR4 group have stronger proliferation ability than other groups ( ), while the CXCR4 inhibitor can reduce this effect. Exosomes control (Exo^Con) can significantly promote the migration of bEnd.3 cells ( ), while there was no significant difference between the Exo^CXCR4 and Exo^Con groups ( ). Exo^CXCR4 can further promote the proliferation and tube formation for the angiogenesis of the endothelium compared with Exo^Con group ( ). In addition, cobalt chloride (COCl2) can increase the expression of β-catenin and Wnt-3, while Exo^Con can reduce the expression of these proteins ( ). Exo^CXCR4 can further attenuate the activation of Wnt-3a/β-catenin pathway ( ). Conclusions. In ischemia/reperfusion injury, Exo^CXCR4 promoted the proliferation and tube formation of microvascular endothelial cells and play an antiapoptotic role via the Wnt-3a/β-catenin pathway.

Lymphocytes play an important role in the immune response after stroke. However, our knowledge of the circulating lymphocytes in ischemic stroke is limited. Herein, we collected the blood samples of clinical ischemic stroke patients to detect the change of lymphocytes from admission to 3 months after ischemic stroke by flow cytometry. A total of 87 healthy controls and 210 patients were enrolled, and the percentages of circulating T cells, CD4⁺ T cells, CD8⁺ T cells, double negative T cells (DNTs), CD4⁺ regulatory T cells (Tregs), CD8⁺ Tregs, B cells and regulatory B cells (Bregs) were measured. Among patients, B cells, Bregs and CD8⁺ Tregs increased significantly, while CD4⁺ Tregs dropped and soon reversed after ischemic stroke. CD4⁺ Tregs, CD8⁺ Tregs, and DNTs also showed high correlations with the infarct volume and neurological scores of patients. Moreover, these lymphocytes enhanced the predictive ability of long-term prognosis of neurological scores when added to basic clinical information. The percentage of CD4⁺ Tregs within lymphocytes showed high correlations with both acute and long-term neurological outcomes, which exhibited a great independent predictive ability. These findings suggest that CD4⁺ Tregs can be a biomarker to predict stroke outcomes and improve existing therapeutic strategies of immunoregulatory lymphocytes.

Introduction Stroke remains a leading cause of death and disability worldwide. Effective and prompt prognostic evaluation is vital for determining the appropriate management strategy. Radiomics is an emerging noninvasive method used to identify the quantitative imaging indicators for predicting important clinical outcomes. This study was conducted to investigate and validate a radiomics nomogram for predicting ischemic stroke prognosis using the modified Rankin scale (mRS). Methods A total of 598 consecutive patients with subacute infarction confirmed by diffusion-weighted imaging (DWI), from January 2018 to December 2019, were retrospectively assessed. They were assigned to the good (mRS ≤ 2) and poor (mRS > 2) functional outcome groups, respectively. Then, 399 patients examined by MR scanner 1 and 199 patients scanned by MR scanner 2 were assigned to the training and validation cohorts, respectively. Infarction lesions underwent manual segmentation on DWI, extracting 402 radiomic features. A radiomics nomogram encompassing patient characteristics and the radiomics signature was built using a multivariate logistic regression model. The performance of the nomogram was evaluated in the training and validation cohorts. Ultimately, decision curve analysis was implemented to assess the clinical value of the nomogram. The performance of infarction lesion volume was also evaluated using univariate analysis. Results Stroke lesion volume showed moderate performance, with an area under the curve (AUC) of 0.678. The radiomics signature, including 11 radiomics features, exhibited good prediction performance. The radiomics nomogram, encompassing clinical characteristics (age, hemorrhage, and 24 h National Institutes of Health Stroke Scale score) and the radiomics signature, presented good discriminatory potential in the training cohort [AUC = 0.80; 95% confidence interval (CI) 0.75–0.86], which was validated in the validation cohort (AUC = 0.73; 95% CI 0.63–0.82). In addition, it demonstrated good calibration in the training (p = 0.55) and validation (p = 0.21) cohorts. Decision curve analysis confirmed the clinical value of this nomogram. Conclusion This novel noninvasive clinical-radiomics nomogram shows good performance in predicting ischemic stroke prognosis.

Stroke is a leading cause of mortality and disability worldwide, expected to result in 61 million disability‐adjusted life‐years in 2020. Rapid diagnostics is the core of stroke management for early prevention and medical treatment. Serum metabolic fingerprints (SMFs) reflect underlying disease progression, predictive of patient phenotypes. Deep learning (DL) encoding SMFs with clinical indexes outperforms single biomarkers, while posing challenges with poor prediction to interpret by feature selection. Herein, rapid computer‐aided diagnosis of stroke is performed using SMF based multi‐modal recognition by DL, to combine adaptive machine learning with a novel feature selection approach. SMFs are extracted by nano‐assisted laser desorption/ionization mass spectrometry (LDI MS), consuming 100 nL of serum in seconds. A multi‐modal recognition is constructed by integrating SMFs and clinical indexes with an enhanced area under curve (AUC) up to 0.845 for stroke screening, compared to single‐modal diagnosis by only SMFs or clinical indexes. The prediction of DL is addressed by selecting 20 key metabolite features with differential regulation through a saliency map approach, shedding light on the molecular mechanisms in stroke. The approach highlights the emerging role of DL in precision medicine and suggests an expanding utility for computational analysis of SMFs in stroke screening.