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The UMLS Metathesaurus, the largest thesaurus in the biomedical domain, provides a representation of biomedical knowledge consisting of concepts classified by semantic type and both hierarchical and non-hierarchical relationships among the concepts. This knowledge has proved useful for many applications including decision support systems, management of patient records, information retrieval (IR) and data mining. Gaining effective access to the knowledge is critical to the success of these applications. This paper describes MetaMap, a program developed at the National Library of Medicine (NLM) to map biomedical text to the Metathesaurus or, equivalently, to discover Metathesaurus concepts referred to in text. MetaMap uses a knowledge intensive approach based on symbolic, natural language processing (NLP) and computational linguistic techniques. Besides being applied for both IR and data mining applications, MetaMap is one of the foundations of NLM's Indexing Initiative System which is being applied to both semi-automatic and fully automatic indexing of the biomedical literature at the library.

High-quality schematic illustrations are fundamental to the publication of scientific achievements in biomedical research, which are crucial for effectively conveying complex biomedical concepts. However, creating such illustrations remains challenging for many researchers due to the need to devote a significant amount of time and effort to accomplish it. To address this need, we present the Generic Diagramming Platform (GDP, https://BioGDP.com), a comprehensive database of professionally crafted biomedical graphics (bio-graphics). Currently, GDP houses 7 562 high-quality bio-graphics, meticulously categorized into 10 major and 77 minor categories. To increase the design efficiency, GDP provides 204 customizable templates derived from an extensive review of over 2000 literature and 7 textbooks. With the interactive drawing platform and user-friendly web interface implemented in GDP, these resources can facilitate the efficient generation of publication-ready illustrations for the biomedical community. Additionally, GDP incorporates a collaborative submission system, allowing researchers to contribute their artwork, fostering a growing diagramming ecosystem, and ensuring continuous database expansion. Overall, we believe that GDP will serve as an invaluable platform, significantly enhancing the efficiency and quality of scientific illustration for biomedical researchers.

Single-cell transcriptomics (scRNA-seq) has become essential for biomedical research over the past decade, particularly in developmental biology, cancer, immunology, and neuroscience. Most commercially available scRNA-seq protocols require cells to be recovered intact and viable from tissue. This has precluded many cell types from study and largely destroys the spatial context that could otherwise inform analyses of cell identity and function. An increasing number of commercially available platforms now facilitate spatially resolved, high-dimensional assessment of gene transcription, known as 'spatial transcriptomics'. Here, we introduce different classes of method, which either record the locations of hybridized mRNA molecules in tissue, image the positions of cells themselves prior to assessment, or employ spatial arrays of mRNA probes of pre-determined location. We review sizes of tissue area that can be assessed, their spatial resolution, and the number and types of genes that can be profiled. We discuss if tissue preservation influences choice of platform, and provide guidance on whether specific platforms may be better suited to discovery screens or hypothesis testing. Finally, we introduce bioinformatic methods for analysing spatial transcriptomic data, including pre-processing, integration with existing scRNA-seq data, and inference of cell-cell interactions. Spatial -omics methods are already improving our understanding of human tissues in research, diagnostic, and therapeutic settings. To build upon these recent advancements, we provide entry-level guidance for those seeking to employ spatial transcriptomics in their own biomedical research.

Titanium (Ti) and its alloys may be processed via advanced powder manufacturing routes such as additive layer manufacturing (or 3D printing) or metal injection moulding. This field is receiving increased attention from various manufacturing sectors including the medical devices sector. It is possible that advanced manufacturing techniques could replace the machining or casting of metal alloys in the manufacture of devices because of associated advantages that include design flexibility, reduced processing costs, reduced waste, and the opportunity to more easily manufacture complex or custom-shaped implants. The emerging advanced manufacturing approaches of metal injection moulding and additive layer manufacturing are receiving particular attention from the implant fabrication industry because they could overcome some of the difficulties associated with traditional implant fabrication techniques such as titanium casting. Using advanced manufacturing, it is also possible to produce more complex porous structures with improved mechanical performance, potentially matching the modulus of elasticity of local bone. While the economic and engineering potential of advanced manufacturing for the manufacture of musculo-skeletal implants is therefore clear, the impact on the biocompatibility of the materials has been less investigated. In this review, the capabilities of advanced powder manufacturing routes in producing components that are suitable for biomedical implant applications are assessed with emphasis placed on surface finishes and porous structures. Given that biocompatibility and host bone response are critical determinants of clinical performance, published studies of in vitro and in vivo research have been considered carefully. The review concludes with a future outlook on advanced Ti production for biomedical implants using powder metallurgy.

Knowledge gained from observational cohort studies has dramatically advanced the prevention and treatment of diseases. Many of these cohorts, however, are small, lack diversity, or do not provide comprehensive phenotype data. The All of Us Research Program plans to enroll a diverse group of at least 1 million persons in the United States in order to accelerate biomedical research and improve health. The program aims to make the research results accessible to participants, and it is developing new approaches to generate, access, and make data broadly available to approved researchers. All of Us opened for enrollment in May 2018 and currently enrolls participants 18 years of age or older from a network of more than 340 recruitment sites. Elements of the program protocol include health questionnaires, electronic health records (EHRs), physical measurements, the use of digital health technology, and the collection and analysis of biospecimens. As of July 2019, more than 175,000 participants had contributed biospecimens. More than 80% of these participants are from groups that have been historically underrepresented in biomedical research. EHR data on more than 112,000 participants from 34 sites have been collected. The All of Us data repository should permit researchers to take into account individual differences in lifestyle, socioeconomic factors, environment, and biologic characteristics in order to advance precision diagnosis, prevention, and treatment.

The National Institutes of Health (NIH) is the world's largest biomedical research agency, with a 75-year record of responding to the nation's key medical challenges. Today, medical science is entering a revolutionary period marked by a shift in focus from acute to chronic diseases, rapidly escalating health care costs, a torrent of biological data generated by the sequencing of the human genome, and the development of advanced high-throughput technologies that allow for the study of vast molecular networks in health and disease. This unique period offers the unprecedented opportunity to identify individuals at risk of disease based on precise molecular knowledge, and the chance to intervene to preempt disease before it strikes. Conceptually, this represents the core scientific challenge of the coming century. The NIH is committed to the discoveries that will change the practice of medicine as we know it in order to meet this challenge. The NIH Roadmap constitutes an important vehicle for generating change-a most critical element of this plan is the reengineering of the national clinical research enterprise. This reinvention will call for the transformation of translational clinical science and for novel interdisciplinary approaches that will advance science and enhance the health of the nation.

Bioactive materials are a kind of materials with unique bioactivities, which can change the cellular behaviors and elicit biological responses from living tissues. Bioactive materials came into the spotlight in the late 1960s when the researchers found that the materials such as bioglass could react with surrounding bone tissue for bone regeneration. In the following decades, advances in nanotechnology brought the new development opportunities to bioactive nanomaterials. Bioactive nanomaterials are not a simple miniaturization of macroscopic materials. They exhibit unique bioactivities due to their nanoscale size effect, high specific surface area, and precise nanostructure, which can significantly influence the interactions with biological systems. Nowadays, bioactive nanomaterials have represented an important and exciting area of research. Current and future applications ensure that bioactive nanomaterials have a high academic and clinical importance. This review summaries the recent advances in the field of bioactive nanomaterials, and evaluate the influence factors of bioactivities. Then, a range of bioactive nanomaterials and their potential biomedical applications are discussed. Furthermore, the limitations, challenges, and future opportunities of bioactive nanomaterials are also discussed.

Magnetic nanoparticles (NPs) are emerging as an important class of biomedical functional nanomaterials in areas such as hyperthermia, drug release, tissue engineering, theranostic, and lab-on-a-chip, due to their exclusive chemical and physical properties. Although some works can be found reviewing the main application of magnetic NPs in the area of biomedical engineering, recent and intense progress on magnetic nanoparticle research, from synthesis to surface functionalization strategies, demands for a work that includes, summarizes, and debates current directions and ongoing advancements in this research field. Thus, the present work addresses the structure, synthesis, properties, and the incorporation of magnetic NPs in nanocomposites, highlighting the most relevant effects of the synthesis on the magnetic and structural properties of the magnetic NPs and how these effects limit their utilization in the biomedical area. Furthermore, this review next focuses on the application of magnetic NPs on the biomedical field. Finally, a discussion of the main challenges and an outlook of the future developments in the use of magnetic NPs for advanced biomedical applications are critically provided.

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly.

High-throughput data production technologies, particularly 'next-generation' DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale.

Abstract The design of advanced, nanostructured materials at the molecular level is of tremendous interest for the scientific and engineering communities because of the broad application of these materials in the biomedical field. Among the available techniques, the layer‐by‐layer assembly method introduced by Decher and co‐workers in 1992 has attracted extensive attention because it possesses extraordinary advantages for biomedical applications: ease of preparation, versatility, capability of incorporating high loadings of different types of biomolecules in the films, fine control over the materials' structure, and robustness of the products under ambient and physiological conditions. In this context, a systematic review of current research on biomedical applications of layer‐by‐layer assembly is presented. The structure and bioactivity of biomolecules in thin films fabricated by layer‐by‐layer assembly are introduced. The applications of layer‐by‐layer assembly in biomimetics, biosensors, drug delivery, protein and cell adhesion, mediation of cellular functions, and implantable materials are addressed. Future developments in the field of biomedical applications of layer‐by‐layer assembly are also discussed.

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ABSTRACT Nanocellulose materials have undergone rapid development in recent years as promising biomedical materials because of their excellent physical and biological properties, in particular their biocompatibility, biodegradability, and low cytotoxicity. Recently, a significant amount of research has been directed toward the fabrication of advanced cellulose nanofibers with different morphologies and functional properties. These nanocellulose fibers are widely applied in medical implants, tissue engineering, drug delivery, wound‐healing, cardiovascular applications, and other medical applications. In this review, we reflect on recent advancements in the design and fabrication of advanced nanocellulose‐based biomaterials (cellulose nanocrystals, bacterial nanocellulose, and cellulose nanofibrils) that are promising for biomedical applications and discuss material requirements for each application, along with the challenges that the materials might face. Finally, we give an overview on future directions of nanocellulose‐based materials in the biomedical field. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132 , 41719.

Native fluorescence, or autofluorescence (AF), consists in the emission of light in the UV-visible, near-IR spectral range when biological substrates are excited with light at suitable wavelength. This is a well-known phenomenon, and the strict relationship of many endogenous fluorophores with morphofunctional properties of the living systems, influencing their AF emission features, offers an extremely powerful resource for directly monitoring the biological substrate condition. Starting from the last century, the technological progresses in microscopy and spectrofluorometry were convoying attention of the scientific community to this phenomenon. In the future, the interest in the autofluorescence will certainly continue. Current instrumentation and analytical procedures will likely be overcome by the unceasing progress in new devices for AF detection and data interpretation, while a progress is expected in the search and characterization of endogenous fluorophores and their roles as intrinsic biomarkers.

Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem.