Many different subpopulations of subcellular extracellular vesicles (EVs) have been described. EVs are released from all cell types and have been shown to regulate normal physiological homeostasis, as well as pathological states by influencing cell proliferation, differentiation, organ homing, injury and recovery, as well as disease progression. In this review, we focus on the bidirectional actions of vesicles from normal and diseased cells on normal or leukemic target cells; and on the leukemic microenvironment as a whole. EVs from human bone marrow mesenchymal stem cells (MSC) can have a healing effect, reversing the malignant phenotype in prostate and colorectal cancer, as well as mitigating radiation damage to marrow. The role of EVs in leukemia and their bimodal cross talk with the encompassing microenvironment remains to be fully characterized. This may provide insight for clinical advances via the application of EVs as potential therapy and the employment of statistical and machine learning models to capture the pleiotropic effects EVs endow to a dynamic microenvironment, possibly allowing for precise therapeutic intervention.

Objectives: The purpose of this study was to systematically review and quantitatively analyze outcomes in operative versus nonoperative management of displaced midshaft clavicle fractures in pediatric and adolescent patients. Data Sources: Using the Preferred Reporting items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, systematic searches of PubMed and EMBASE were conducted to identify English-language studies reporting outcomes in displaced pediatric midshaft clavicle fractures from 1997 to 2018. Study Selection: Studies that reported on outcomes of operative and/or nonoperative treatment of displaced midshaft clavicle fractures in patients younger than 19 years were included. Data Extraction: Patient and treatment characteristics, union rates, time to union, time to return to activity, patient-reported outcome measures, and complications were extracted. Data Synthesis: All extracted data were recorded and qualitatively compared. QuickDASH (Quick Disabilities of the Arm, Shoulder, and Hand) scores and Constant scores were pooled using random-effects modeling and compared among studies, which adequately reported data for hypothesis testing. Conclusions: Three thousand eight hundred ten articles were identified, and 12 met inclusion criteria. These studies encompassed 497 patients with an average age of 14.1 years (8–18 years, range). Both operative and nonoperative management of displaced midshaft clavicle fractures in this population provide excellent rates of union and patient-reported outcome measures. Compared with nonoperative management, operative management yielded faster return to activity, superior Constant scores, and equal QuickDASH scores. Operative management had higher complication rates and complications that required secondary operative treatment (mostly related to implant prominence). Level of Evidence: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

This is an extraordinary time in cell biology with evolving data pushing a reconsideration of the stability of cell systems and the regulatory mechanisms underlying cell phenotypes, especially the functional cell phenotypes. In this chapter, we will explore new insights into stem cell and extracellular vesicle biology with a focus on the role of extracellular vesicles in normal stem cell physiology as well as in various disease states. Extracellular vesicles (EVs) are being recognized as influential mediators of cellular function and potential experimental therapeutic strategies for a number of disorders outlined in this review. An evolving paradigm indicates a dynamic flux of EV populations within these disease states. We conclude our discussion of EV by extending our knowledge of robust EV biology toward disease detection and prognostication. Characterizing the biophysical and functional changes of vesicles amid disease progression or regression enables investigators to merge this information flux with existing deep learning computational and statistical techniques-allowing knowledge to be abstracted from large data sets profiling the biology of EVs within various disease states. Understanding how EV population shifts represent disease regression or progression creates paramount potential for EVs as salient and clinically relevant diagnostic and prognosticating tools.