Abstract
Aims
We have shown that extracellular vesicles (EVs) secreted by embryonic stem cell-derived cardiovascular progenitor cells (Pg) recapitulate the therapeutic effects of their parent cells ...in a mouse model of chronic heart failure (CHF). Our objectives are to investigate whether EV released by more readily available cell sources are therapeutic, whether their effectiveness is influenced by the differentiation state of the secreting cell, and through which mechanisms they act.
Methods and results
The total EV secreted by human induced pluripotent stem cell-derived cardiovascular progenitors (iPSC-Pg) and human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) were isolated by ultracentrifugation and characterized by Nanoparticle Tracking Analysis, western blot, and cryo-electron microscopy. In vitro bioactivity assays were used to evaluate their cellular effects. Cell and EV microRNA (miRNA) content were assessed by miRNA array. Myocardial infarction was induced in 199 nude mice. Three weeks later, mice with left ventricular ejection fraction (LVEF) ≤ 45% received transcutaneous echo-guided injections of iPSC-CM (1.4 × 106, n = 19), iPSC-Pg (1.4 × 106, n = 17), total EV secreted by 1.4 × 106 iPSC-Pg (n = 19), or phosphate-buffered saline (control, n = 17) into the peri-infarct myocardium. Seven weeks later, hearts were evaluated by echocardiography, histology, and gene expression profiling, blinded to treatment group. In vitro, EV were internalized by target cells, increased cell survival, cell proliferation, and endothelial cell migration in a dose-dependent manner and stimulated tube formation. Extracellular vesicles were rich in miRNAs and most of the 16 highly abundant, evolutionarily conserved miRNAs are associated with tissue-repair pathways. In vivo, EV outperformed cell injections, significantly improving cardiac function through decreased left ventricular volumes (left ventricular end systolic volume: −11%, P < 0.001; left ventricular end diastolic volume: −4%, P = 0.002), and increased LVEF (+14%, P < 0.0001) relative to baseline values. Gene profiling revealed that EV-treated hearts were enriched for tissue reparative pathways.
Conclusion
Extracellular vesicles secreted by iPSC-Pg are effective in the treatment of CHF, possibly, in part, through their specific miRNA signature and the associated stimulation of distinct cardioprotective pathways. The processing and regulatory advantages of EV could make them effective substitutes for cell transplantation.
Today, machine-learning software is used to help make decisions that affect people's lives. Some people believe that the application of such software results in fairer decisions because, unlike ...humans, machine-learning software generates models that are not biased. Think again. Machine-learning software is also biased, sometimes in similar ways to humans, often in different ways. While fair model- assisted decision making involves more than the application of unbiased models-consideration of application context, specifics of the decisions being made, resolution of conflicting stakeholder viewpoints, and so forth-mitigating bias from machine-learning software is important and possible but difficult and too often ignored.
Biostatisticians with advanced degrees are highly sought after. Employment opportunities in the fields of mathematics and statistics are expected to increase dramatically by 2028. Underrepresentation ...of minorities in biostatistics has been a persistent problem, yielding a demographic landscape that differs substantially from the general U.S. population. In some instances, students may have the appropriate quantitative skills, but are unaware of biostatistics and in other instances, students may not yet have the appropriate quantitative background, but are intellectually capable and willing to shore up those skills once they learn about biostatistics as a viable, exciting career option. Therefore, to ensure robust scientific advancement, there must be a concerted effort to increase the pipeline of intellectually talented persons available with exposure to the appropriate quantitative skills who are interested in careers in biostatistics. The overarching goal of this article is to discuss the development, implementation, and impact of a federally funded pipeline initiative aimed at increasing the number of underrepresented minorities successful in graduate training and professional careers in biostatistics as well as establishing effective mentoring and networking relationships. Our findings provide a roadmap for the development of sustainable initiatives to promote diversity in biostatistics and science, technology, engineering, and mathematics fields more broadly. Supplementary files for this article are available online.
Today, AI is increasingly being used in many high-stakes decision-making applications in which fairness is an important concern. Already, there are many examples of AI being biased and making ...questionable and unfair decisions. The AI research community has proposed many methods to measure and mitigate unwanted biases, but few of them involve inputs from human policy makers. We argue that because different fairness criteria sometimes cannot be simultaneously satisfied, and because achieving fairness often requires sacrificing other objectives such as model accuracy, it is key to acquire and adhere to human policy makers' preferences on how to make the tradeoff among these objectives. In this paper, we propose a framework and some exemplar methods for eliciting such preferences and for optimizing an AI model according to these preferences.
This paper explores the design of visualizations that support mandated organizational compliance processes. We draw on the research literature to show how visualizations can operate as effective user ...interfaces for complex, distributed processes. We argue that visualizations can reduce the complexity of such processes, making them easier to manage, and can facilitate the communication and collaboration that are critical to supporting compliance. We describe the design and pilot deployment of a visualization that supports the IBM Sarbanes-Oxley Act compliance process, discussing design alternatives, the final design, its deployment, and lessons learned. PUBLICATION ABSTRACT
Musculoskeletal conditions are extremely common and include more than 150 different diseases and syndromes, which are usually associated with pain and loss of function. In the developed world, where ...these conditions are already the most frequent cause of physical disability, ageing of the most populous demographic groups will further increase the burden these conditions impose. In the developing world, successful care of childhood and communicable diseases and an increase in road traffic accidents is shifting the burden to musculoskeletal and other noncommunicable conditions. To help better prepare nations for the increase in disability brought about by musculoskeletal conditions, a Scientific Group meeting was held to map out the burden of the most prominent musculoskeletal conditions at the start of the Bone and Joint Decade. In particular, the Group gathered data on the incidence and prevalence of rheumatoid arthritis, osteoarthritis, osteoporosis, major limb trauma and spinal disorders. Data were collected and organized by world region, gender and age groups to assist with the ongoing WHO Global Burden of Disease 2000 study. The Group also considered what is known about the severity and course of these conditions, along with their economic impact. The most relevant domains to assess and monitor the consequences of these conditions were identified and used to describe health states for the different stages of the conditions. Instruments that measure these most important domains for the different conditions were recommended. It is clear from data collated that the impact from musculoskeletal conditions and trauma varies among different parts of the world and is influenced by social structure, expectation and economics, and that it is most difficult to measure impact in less developed nations, where the predicted increase is greatest.
As artificial intelligence and machine learning algorithms become increasingly prevalent in society, multiple stakeholders are calling for these algorithms to provide explanations. At the same time, ...these stakeholders, whether they be affected citizens, government regulators, domain experts, or system developers, have different explanation needs. To address these needs, in 2019, we created AI Explainability 360 (Arya et al. 2020), an open source software toolkit featuring ten diverse and state-of-the-art explainability methods and two evaluation metrics. This paper examines the impact of the toolkit with several case studies, statistics, and community feedback. The different ways in which users have experienced AI Explainability 360 have resulted in multiple types of impact and improvements in multiple metrics, highlighted by the adoption of the toolkit by the independent LF AI & Data Foundation. The paper also describes the flexible design of the toolkit, examples of its use, and the significant educational material and documentation available to its users.
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