A standardized method for plasma extracellular vesicle isolation and size distribution analysis

Therapeutic potential of extracellular vesicles derived from human amniotic epithelial cells for perinatal cerebral and pulmonary injury

Lung and brain injury that occurs during the perinatal period leads to lifelong disability and is often driven and/or exacerbated by inflammation. Human amniotic epithelial cells (hAEC), which demonstrate immunomodulatory, anti-fibrotic, and regenerative capabilities, are being explored as a therapeutic candidate for perinatal injury. However, limitations regarding scalable manufacturing, storage, transport, and dose-related toxicity have impeded clinical translation. Isolated therapeutic extracellular vesicles (EVs) from stem and stem-like cells are thought to be key paracrine mediators of therapeutic efficacy. The unique characteristics of EVs suggest that they potentially circumvent the limitations of traditional cell-based therapies. However, given the novelty of EVs as a therapeutic, recommendations around ideal methods of production, isolation, storage, and delivery have not yet been created by regulatory agencies. In this concise review, we discuss the pertinence and limitations of cell-based therapeutics in perinatal medicine. We also review the preclinical evidence supporting the use of therapeutic EVs for perinatal therapy. Further, we summarize the arising considerations regarding adequate cell source, biodistribution, isolation and storage methods, and regulatory roadblocks for the development of therapeutic EVs.

Blood Biomarkers for the Management of Mild Traumatic Brain Injury in Clinical Practice

BACKGROUND

Despite the use of validated guidelines in the management of mild traumatic brain injury (mTBI), processes to limit unnecessary brain scans are still not sufficient and need to be improved. The use of blood biomarkers represents a relevant adjunct to identify patients at risk for intracranial injury requiring computed tomography (CT) scan.

CONTENT

Biomarkers currently recommended in the management of mTBI in adults and children are discussed in this review. Protein S100 beta (S100B) is the best-documented blood biomarker due to its validation in large observational and interventional studies. Glial fibrillary acidic protein (GFAP) and ubiquitin carboxyterminal hydrolase L-1 (UCH-L1) have also recently demonstrated their usefulness in patients with mTBI. Preanalytical, analytical, and postanalytical performance are presented to aid in their interpretation in clinical practice. Finally, new perspectives on biomarkers and mTBI are discussed.

SUMMARY

In adults, the inclusion of S100B in Scandinavian and French guidelines has reduced the need for CT scans by at least 30%. S100B has significant potential as a diagnostic biomarker, but limitations include its rapid half-life, which requires blood collection within 3 h of trauma, and its lack of neurospecificity. In 2018, the FDA approved the use of combined determination of GFAP and UCH-L1 to aid in the assessment of mTBI. Since 2022, new French guidelines also recommend the determination of GFAP and UCH-L1 in order to target a larger number of patients (sampling within 12 h post-injury) and optimize the reduction of CT scans. In the future, new cut-offs related to age and promising new biomarkers are expected for both diagnostic and prognostic applications.

New Directions in Diagnostics for Aortic Aneurysms: Biomarkers and Machine Learning

This review article presents an appraisal of pioneering technologies poised to revolutionize the diagnosis and management of aortic aneurysm disease, with a primary focus on the thoracic aorta while encompassing insights into abdominal manifestations. Our comprehensive analysis is rooted in an exhaustive survey of contemporary and historical research, delving into the realms of machine learning (ML) and computer-assisted diagnostics. This overview draws heavily upon relevant studies, including Siemens' published field report and many peer-reviewed publications. At the core of our survey lies an in-depth examination of ML-driven diagnostic advancements, dissecting an array of algorithmic suites to unveil the foundational concepts anchoring computer-assisted diagnostics and medical image processing. Our review extends to a discussion of circulating biomarkers, synthesizing insights gleaned from our prior research endeavors alongside contemporary studies gathered from the PubMed Central database. We elucidate the prevalent challenges and envisage the potential fusion of AI-guided aortic measurements and sophisticated ML frameworks with the computational analyses of pertinent biomarkers. By framing current scientific insights, we contemplate the transformative prospect of translating fundamental research into practical diagnostic tools. This narrative not only illuminates present strides, but also forecasts promising trajectories in the clinical evaluation and therapeutic management of aortic aneurysm disease.

Extracellular vesicles in cardiomyopathies: A narrative review

Extracellular vesicles (EVs) are membrane-bound particles released by all cells under physiological and pathological conditions. EVs constitute a potential tool to unravel cell-specific pathophysiological mechanisms at the root of disease states and retain the potential to act as biomarkers for cardiac diseases. By being able to carry bioactive cargo (such as proteins and miRNAs), EVs harness great potential as accessible "liquid biopsies", given their ability to reflect the state of their cell of origin. Cardiomyopathies encompass a variety of myocardial disorders associated with mechanical, functional and/or electric dysfunction. These diseases exhibit different phenotypes, including inappropriate ventricular hypertrophy, dilatation, scarring, fibro-fatty replacement, dysfunction, and may stem from multiple aetiologies, most often genetic. Thus, the aims of this narrative review are to summarize the current knowledge on EVs and cardiomyopathies (e.g., hypertrophic, dilated and arrhythmogenic), to elucidate the potential role of EVs in the paracrine cell-to-cell communication among cardiac tissue compartments, in aiding the diagnosis of the diverse subtypes of cardiomyopathies in a minimally invasive manner, and finally to address whether certain molecular and phenotypical characteristics of EVs may correlate with cardiomyopathy disease phenotype and severity.