Extracellular Vesicles Treatment Induces Pro‐resolutive Microglial Changes in Experimental Models of Ischemic Stroke: A Systematic Review and Meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Ischemic stroke (IS) is a risk factor for developing Alzheimer's disease (AD). In this context, microglial activation is a shared cellular response to these two conditions that can be either beneficial or detrimental. Previous research has established that mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) treatment leads to enhanced functional recovery and reduced brain infarct volume in animal IS models. However, current literature findings are unclear when addressing the effects of MSC-EVs treatment on microglial activation. Thus, we aimed to investigate how MSC-EVs treatment alters microglial activation parameters in IS models. METHOD: The protocol of this systematic review was registered in PROSPERO (CRD42023463152) and followed the PRISMA 2020 statement. We searched EMBASE, PubMed, and Web of Science from database inception to October 2023 for studies with animal or cell culture IS models using MSC-EVs as intervention and measuring microglial activation outcomes compared to control. We performed a random-effects meta-analysis using standardized mean differences (SMD) as the effect measure with the metafor and metaviz packages in R (v4.2.1) (FDR-adjusted p-value<0.05). RESULT: The database search identified 294 records, from which 27 were included (Fig. 1). Meta-analysis showed that in vivo MSC-EVs treatment resulted in a lower number of total microglia (Iba1+ cells) (SMD = -1.45 [-2.19,-0.71 95%CI] p<0.001, Fig. 2A) and CD16+ microglia (SMD = -1.84 [-2.62,-1.05 95%CI] p<0.001, Fig. 2B), but in a higher number of CD206+ microglia (SMD = 1.95 [1.01,2.88 95%CI] p<0.001, Fig. 2C) in the brain across different IS models and age groups. In microglia cell cultures submitted to oxygen-glucose deprivation, MSC-EVs treatment decreased the levels of TNF-α (SMD = -3.32 [-4.95,-1.69 95%CI] p<0.001, Fig. 3A), IL-1β (SMD = -3.45 [-5.57,-1.32 95%CI] p<0.001, Fig. 3B), and IL-6 (SMD = -2.95 [-4.50,-1.40 95%CI] p<0.001, Fig. 3C) in the culture medium, while increasing the gene expression levels of Arg-1 (SMD = 5.41[3.54,7.29 95%CI] p<0.001, Fig. 3D). CONCLUSION: We demonstrated that MSC-EVs treatment in IS models reduces the expression of pro-inflammatory microglial activation markers (CD16) and cytokines (TNF-α, IL-1β, IL-6) while increasing the expression of anti-inflammatory markers (CD206, Arg-1). Our results suggest that MSC-EVs treatment modulates microglia towards a pro-resolutive state, potentially contributing to the recovery of damaged brain tissue in IS and, consequently, in AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".