Ischemic stroke, a significant neurovascular disorder, currently lacks effective restorative medication. However, recently developed nanomedicines bring renewed promise for alleviating ischemia’s effects and facilitating the healing of neurological and physical functions. The aim of this systematic review was to evaluate the efficacy of nanotherapies in animal models of stroke and their potential impact on future stroke therapies. We also assessed the scientific quality of current research focused on nanoparticle-based treatments for ischemic stroke in animal models. We summarized the effectiveness of nanotherapies in these models, considering multiple factors such as their anti-inflammatory, antioxidant, and angiogenetic properties, as well as their safety and biodistribution. We conclude that the application of nanomedicines may reduce infarct size and improve neurological function post-stroke without causing significant organ toxicity.

Aim: Stroke is one of the leading causes of death and disability worldwide. Plasma biomarkers have long been used to evaluate physiological or pathological processes and to make predictions about the outcome of stroke patients. The current systematic review is focused on genetic plasma biomarkers as a new potential prognostic indicator for post-stroke recovery. The aim of the present systematic review is to assess the potential of genetic plasma biomarkers associated with stroke to predict post-stroke recovery. Methods: The search strategy used PubMed and Web of Science databases to identified 166 studies that investigated genetic plasma biomarkers in patients with stroke between 2017 and 2021. However, only 21 of them met the inclusion criteria. Results: The identified genetic biomarkers can be divided into: (i) serum/plasma circular RNA (circRNA) associated with stroke onset or recurrence (5; 23.80%), (ii) genetic polymorphisms associated with the atherosclerotic process and stroke recurrence (6; 28.57%), (iii) serum/plasma long non-coding RNA (lncRNA) levels involved in immunity/inflammatory processes (4; 19.04%), (iv) marker of DNA methylation associated with stroke onset and outcome (3; 14.28%), and (v) proteins and pathways of stroke identified by serum/ plasma proteomics/genomics analysis (3; 14.28%). Conclusions: Overall, more than 100 potential biomarkers were found and the data suggest that combinations of plasma genetic biomarkers might be used as a better predictor for stroke.