Gelatin methacryloyl microneedle loaded with 3D-MSC-Exosomes for the protection of ischemia-reperfusion.

Exosomes (Exo) generated from mesenchymal stem cells (MSCs) have great therapeutic potential in ischemia-reperfusion treatment. For best therapeutic effect, high quality Exo product and effective delivery system are indispensable. In this study, we developed a new strategy for ischemia-reperfusion recovery by combining MSCs 3D (3D-MSC) culturing technology to generate Exo (3D-MSC-Exo) and microneedle for topical delivery. Firstly, primary MSCs from neonatal mice were isolated and 3D cultured with gelatin methacryloyl (GelMA) hydrogel to prepare 3D-MSC-Exo. The 3D-MSC showed better viability and 3D-MSC-Exo exhibited more effective effects of reducing neuroinflammation, inhibiting glial scarring, and promoting angiogenesis. Subsequently, the biocompatible GelMA was used to construct microneedles for 3D-Exo delivery (GelMA-MN@3D-Exo). The results demonstrated GelMA microneedles had excellent 3D-Exo loading capacity and enabled continuous 3D-Exo release to maintain effective therapeutic concentrations. Furthermore, the rat middle cerebral artery occlusion (MCAO) model was established to evaluate the therapeutic effect of GelMA-MN@3D-Exo in ischemia-reperfusion in vivo. Animal experiments showed that the GelMA-MN@3D-Exo system could effectively reduce the local neuroinflammatory reaction, promote angiogenesis and minimize glial scar proliferation in ischemia-reperfusion. The underlying reasons for the stronger neuroprotective effect of 3D-Exo was further studied using mass spectrometry and transcriptome assays, verifying their effects on immune regulation and cell proliferation. Taken together, our findings demonstrated that GelMA-MN@3D-Exo microneedle can effectively attenuate ischemia-reperfusion cell damage in the MCAO model, which provides a promising therapeutic strategy for ischemia-reperfusion recovery.

Identifying global research trends on inflammation associated with traumatic brain injury by bibliometric and visualized analysis.

Background: Traumatic brain injury (TBI) is a catastrophic disease involving complex inflammatory processes. This study aimed to quantitatively analyze and visualize the global research trends on inflammation associated with TBI. Methods: All publications concerning TBI and inflammation published from 2007 to 2021 were retrieved from the Web of Science Core Collection database. Key visualization and statistical analysis were calculated and evaluated using VOSviewer, CiteSpace, R package "bibliometrix," and an online bibliometric analysis platform. Results: From 2007 to 2021, 15,138 authors from 2860 institutions in 77 countries/regions published 3154 articles on inflammation associated with TBI in 786 academic journals. The research output has significantly increased over the years despite a minor fluctuation. Among the countries, the United States showed the highest output (43.50%) with the most total citations (62,791). The author with the most published articles was Cox CS (30 articles with h-index = 20), and the most popular journal in the field was the Journal of Neurotrauma (190 papers, cited 6433 times). The high-frequency keywords were "post-traumatic brain injury," "brain edema," and "glial activation." Moreover, high-frequency keywords analysis indicated that various inflammatory cells contributed to neuroinflammation, neuroprotection, and oxidative stress after TBI. Conclusion: This study revealed the research trends, hotspots, and emerging topics in inflammation associated with TBI by quantitative and visualized analysis. The current research focuses on the crosstalk between various inflammatory cells and the brain and the associated mechanisms. This study presents the research landscape and inspires future research on inflammation associated with TBI.

Bibliometric and Visualized Analysis of Global Evolution of Research in Lung Ultrasound: A Rapidly Developing Field.

BACKGROUND: Lung ultrasound (LUS) is gaining recognition as an indispensable diagnostic tool in critical care. OBJECTIVE: The study aimed to characterize the global research landscape and trend of LUS with quantification and visualization approaches. METHODS: Documents related to LUS published between 2007 and 2023 were selected from the Web of Science Core Collection and identified. Visualization and statistical analysis were conducted with the VOSviewer 1.6.18, CiteSpace 5.7.R5, and Bibliometrix 4.1.0 Package, including analysis of the trend of global publications, prominent countries, active institutions, and funding agencies, key authors and journals, co-cited references, and keywords. RESULTS: A total of 3010 publications, including 2434 articles and 576 reviews, were retrieved. The output of LUS-related research has increased steadily over the years, especially after 2018. Italy (n=756; 25.12%) has shown the highest output, being the country with the highest total citations (23423 times). The most influential author was Gargani Luna with 52 documents, who worked at the Consiglio Nazionale delle Ricerche. Chest and Intensive Care Medicine with high citations and impact factor scores were the most influential journals. Besides "lung ultrasonography", the keywords developed included "coronavirus disease 2019 (COVID-19)", "acute respiratory distress syndrome", and "acute heart failure". CONCLUSION: Research output on LUS has increased steadily, especially after 2018. Italy and the United States are staying ahead in this field. Research collaboration still needs to be strengthened. This comprehensive analysis has presented the global research landscape and trends of LUS-related research, providing valuable information for researchers to pursue further exploration.

Integrated analysis of C3AR1 and CD163 associated with immune infiltration in intracranial aneurysms pathogenesis.

Background: To identify potential immune-related biomarkers, molecular mechanism, and therapeutic agents of intracranial aneurysms (IAs). Methods: We identified the differentially expressed genes (DEGs) between IAs and control samples from GSE75436, GSE26969, GSE6551, and GSE13353 datasets. We used weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis to identify immune-related hub genes. We evaluated the expression of hub genes by using qRT-PCR analysis. Using miRNet, NetworkAnalyst, and DGIdb databases, we analyzed the regulatory networks and potential therapeutic agents targeting hub genes. Least absolute shrinkage and selection operator (LASSO) logistic regression was performed to identify optimal biomarkers among hub genes. The diagnostic value was validated by external GSE15629 dataset. Results: We identified 227 DEGs and 22 differentially infiltrating immune cells between IAs and control samples from GSE75436, GSE26969, GSE6551, and GSE13353 datasets. We further identified 41 differentially expressed immune-related genes (DEIRGs), which were primarily enriched in the chemokine-mediated signaling pathway, myeloid leukocyte migration, endocytic vesicle membrane, chemokine receptor binding, chemokine activity, and viral protein interactions with cytokines and their receptors. Among 41 DEIRGs, 10 hub genes including C3AR1, CD163, CCL4, CXCL8, CCL3, TLR2, TYROBP, C1QB, FCGR3A, and FCGR1A were identified with good diagnostic values (AUC >0.7). Hsa-mir-27a-3p and transcription factors, including YY1 and GATA2, were identified the primary regulators of hub genes. 92 potential therapeutic agents targeting hub genes were predicted. C3AR1 and CD163 were finally identified as the best diagnostic biomarkers using LASSO logistic regression (AUC = 0.994). The diagnostic value of C3AR1 and CD163 was validated by the external GSE15629 dataset (AUC = 0.914). Conclusions: This study revealed the importance of C3AR1 and CD163 in immune infiltration in IAs pathogenesis. Our finding provided a valuable reference for subsequent research on the potential targets for molecular mechanisms and intervention of IAs.

EMG-Torque Relation in Chronic Stroke: A Novel EMG Complexity Representation With a Linear Electrode Array.

This study examines the electromyogram (EMG)-torque relation for chronic stroke survivors using a novel EMG complexity representation. Ten stroke subjects performed a series of submaximal isometric elbow flexion tasks using their affected and contralateral arms, respectively, while a 20-channel linear electrode array was used to record surface EMG from the biceps brachii muscles. The sample entropy (SampEn) of surface EMG signals was calculated with both global and local tolerance schemes. A regression analysis was performed between SampEn of each channel's surface EMG and elbow flexion torque. It was found that a linear regression can be used to well describe the relation between surface EMG SampEn and the torque. Each channel's root mean square (RMS) amplitude of surface EMG signal in the different torque level was computed to determine the channel with the highest EMG amplitude. The slope of the regression (observed from the channel with the highest EMG amplitude) was smaller on the impaired side than on the nonimpaired side in 8 of the 10 subjects, regardless of the tolerance scheme (global or local) and the range of torques (full or matched range) used for comparison. The surface EMG signals from the channels above the estimated muscle innervation zones demonstrated significantly lower levels of complexity compared with other channels between innervation zones and muscle tendons. The study provides a novel point of view of the EMG-torque relation in the complexity domain, and reveals its alterations post stroke, which are associated with complex neural and muscular changes post stroke. The slope difference between channels with regard to innervation zones also confirms the relevance of electrode position in surface EMG analysis.