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At least 55 records · Page 3

A pre-training and self-training approach for biomedical named entity recognition

Named entity recognition (NER) is a key component of many scientific literature mining tasks, such as information retrieval, information extraction, and question answering; however, many modern approaches require large amounts of labeled training data in order to be effective. This severely limits the effectiveness of NER models in applications where expert annotations are difficult and expensive to obtain. In this work, we explore the effectiveness of transfer learning and semi-supervised self-training to improve the performance of NER models in biomedical settings with very limited labeled data (250-2000 labeled samples). We first pre-train a BiLSTM-CRF and a BERT model on a very large general biomedical NER corpus such as MedMentions or Semantic Medline, and then we fine-tune the model on a more specific target NER task that has very limited training data; finally, we apply semi-supervised self-training using unlabeled data to further boost model performance. We show that in NER tasks that focus on common biomedical entity types such as those in the Unified Medical Language System (UMLS), combining transfer learning with self-training enables a NER model such as a BiLSTM-CRF or BERT to obtain similar performance with the same model trained on 3x-8x the amount of labeled data. We further show that our approach can also boost performance in a low-resource application where entities types are more rare and not specifically covered in UMLS.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Quantum Computing for Biomedical Computational and Data Sciences: A Joint DOE-NIH Roundtable

The overlap of quantum computing and biomedical research, while less explored, presents significant near-term opportunities. The Department of Energy (DOE) and the National Institutes of Health (NIH) are interested in exploiting the DOE community’s capabilities and expertise in quantum computing to potentially advance biomedical research, targeting fundamental studies of biological and molecular structures, understanding of human health as well as mental and physical disorders and diseases, and deriving insights from clinical data. NIH’s approach to quantum computing is guided by its Strategic Plan for Data Science, emphasizing the importance of findable, accessible, interoperable, and reusable (FAIR) data assets, security and privacy of data, and efficient computing and storage. DOE’s Office of Science (SC), and more specifically the Advanced Scientific Computing Research (ASCR) program, supports quantum information science (QIS) research, contributing to a unique portfolio of quantum computing and communications expertise. This roundtable was assembled to consider the opportunities and challenges in the near-, medium-, and long-term at the intersection of quantum computing, data science, and biomedical research and how these could be addressed through inter-agency collaboration and multi-disciplinary partnerships.

59 BASIC BIOLOGICAL SCIENCES↗

Assistance to NASA in biomedical areas of the technology utilization program

The applications of aerospace technology to biomedical research are reported. The medical institutions participating in the Biomedical Applications Program are listed along with the institutions currently utilizing the services of the Southwest Research Institute Biomedical Applications Team. Significant accomplishments during this period include: ultra-low bandpass amplifier for gastro-intestinal electric potentials; non-encumbering EEG electrode assembly suitable for long term sleep research; accurate cardiac telemetry system for active subjects; warning system for the deaf; tracking cane for the blind; and an improved control mechanism to expand the self-sufficiency of quadriplegics.

Culclasure, D. F.↗

Biomedical technology transfer applications of NASA science and technology

The identification and solution of research and clinical problems in cardiovascular medicine which were investigated by means of biomedical data transfer are reported. The following are sample areas that were focused upon by the Stanford University Biomedical Technology Transfer Team: electrodes for hemiplegia research; vectorcardiogram computer analysis; respiration and phonation electrodes; radiotelemetry of intracranial pressure; and audiotransformation of the electrocardiographic signal. It is concluded that this biomedical technology transfer is significantly aiding present research in cardiovascular medicine.

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The Application of Integrated Knowledge-based Systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through the Biomedical Risk Assessment Intelligent Network (BRAIN), an integrated network of both human and computer elements. The BRAIN will function as an advisor to flight surgeons by assessing the risk of in-flight biomedical problems and recommending appropriate countermeasures. This paper describes the joint effort among various NASA elements to develop BRAIN and an Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of the following: (1) knowledge acquisition; (2) integration of IDRA components; (3) use of expert systems to automate the biomedical prediction process; (4) development of a user-friendly interface; and (5) integration of the IDRA prototype and Exercise Countermeasures Intelligent System (ExerCISys). Because the C Language, CLIPS (the C Language Integrated Production System), and the X-Window System were portable and easily integrated, they were chosen as the tools for the initial IDRA prototype. The feasibility was tested by developing an IDRA prototype that predicts the individual risk of influenza. The application of knowledge-based systems to risk assessment is of great market value to the medical technology industry.

Loftin, Karin C.↗

NASA Ames Research Center R and D Services Directorate Biomedical Systems Development

The Ames Research Center R&D Services Directorate teams with NASA, other government agencies and/or industry investigators for the development, design, fabrication, manufacturing and qualification testing of space-flight and ground-based experiment hardware for biomedical and general aerospace applications. In recent years, biomedical research hardware and software has been developed to support space-flight and ground-based experiment needs including the E 132 Biotelemetry system for the Research Animal Holding Facility (RAHF), E 100 Neurolab neuro-vestibular investigation systems, the Autogenic Feedback Systems, and the Standard Interface Glove Box (SIGB) experiment workstation module. Centrifuges, motion simulators, habitat design, environmental control systems, and other unique experiment modules and fixtures have also been developed. A discussion of engineered systems and capabilities will be provided to promote understanding of possibilities for future system designs in biomedical applications. In addition, an overview of existing engineered products will be shown. Examples of hardware and literature that demonstrate the organization's capabilities will be displayed. The Ames Research Center R&D Services Directorate is available to support the development of new hardware and software systems or adaptation of existing systems to meet the needs of academic, commercial/industrial, and government research requirements. The Ames R&D Services Directorate can provide specialized support for: System concept definition and feasibility Mathematical modeling and simulation of system performance Prototype hardware development Hardware and software design Data acquisition systems Graphical user interface development Motion control design Hardware fabrication and high-fidelity machining Composite materials development and application design Electronic/electrical system design and fabrication System performance verification testing and qualification.

Pollitt, J.↗

National Space Biomedical Research Institute

In June 1996, NASA released a Cooperative Agreement Notice (CAN) inviting proposals to establish a National Space Biomedical Research Institute (9-CAN-96-01). This CAN stated that: The Mission of the Institute will be to lead a National effort for accomplishing the integrated, critical path, biomedical research necessary to support the long term human presence, development, and exploration of space and to enhance life on Earth by applying the resultant advances in human knowledge and technology acquired through living and working in space. The Institute will be the focal point of NASA sponsored space biomedical research. This statement has not been amended by NASA and remains the mission of the NSBRI.

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National Space Biomedical Research Institute

NSBRI partners with NASA to develop countermeasures against the deleterious effects of long duration space flight. NSBRI's science and technology projects are directed toward this goal, which is accomplished by: 1. Designing, testing and validating effective countermeasures to address the biological and environmental impediments to long-term human space flight. 2. Defining the molecular, cellular, organ-level, integrated responses and mechanistic relationships that ultimately determine these impediments, where such activity fosters the development of novel countermeasures. 3. Establishing biomedical support technologies to maximize human performance in space, reduce biomedical hazards to an acceptable level and deliver quality medical care. 4. Transferring and disseminating the biomedical advances in knowledge and technology acquired through living and working in space to the general benefit of humankind; including the treatment of patients suffering from gravity- and radiation-related conditions on Earth. and 5. ensuring open involvement of the scientific community,industry and the public in the Institute's activities and fostering a robust collaboration with NASA, particularly through JSC.

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NASA Biomedical Informatics Capabilities and Needs

To improve on-orbit clinical capabilities by developing and providing operational support for intelligent, robust, reliable, and secure, enterprise-wide and comprehensive health care and biomedical informatics systems with increasing levels of autonomy, for use on Earth, low Earth orbit & exploration class missions. Biomedical Informatics is an emerging discipline that has been defined as the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information. The end objective of biomedical informatics is the coalescing of data, knowledge, and the tools necessary to apply that data and knowledge in the decision-making process, at the time and place that a decision needs to be made.

Johnson-Throop, Kathy A.↗

Legacy of Biomedical Research During the Space Shuttle Program

The Space Shuttle Program provided many opportunities to study the role of spaceflight on human life for over 30 years and represented the longest and largest US human spaceflight program. Outcomes of the research were understanding the effect of spaceflight on human physiology and performance, countermeasures, operational protocols, and hardware. The Shuttle flights were relatively short, < 16 days and routinely had 4 to 6 crewmembers for a total of 135 flights. Biomedical research was conducted on the Space Shuttle using various vehicle resources. Specially constructed pressurized laboratories called Spacelab and SPACEHAB housed many laboratory instruments to accomplish experiments in the Shuttle s large payload bay. In addition to these laboratory flights, nearly every mission had dedicated human life science research experiments conducted in the Shuttle middeck. Most Shuttle astronauts participated in some life sciences research experiments either as test subjects or test operators. While middeck experiments resulted in a low sample per mission compared to many Earth-based studies, this participation allowed investigators to have repetition of tests over the years on successive Shuttle flights. In addition, as a prelude to the International Space Station (ISS), NASA used the Space Shuttle as a platform for assessing future ISS hardware systems and procedures. The purpose of this panel is to provide an understanding of science integration activities required to implement Shuttle research, review biomedical research, characterize countermeasures developed for Shuttle and ISS as well as discuss lessons learned that may support commercial crew endeavors. Panel topics include research integration, cardiovascular physiology, neurosciences, skeletal muscle, and exercise physiology. Learning Objective: The panel provides an overview from the Space Shuttle Program regarding research integration, scientific results, lessons learned from biomedical research and countermeasure development.

Hayes, Judith C.↗

Rediscovering Apollo Biomedical Data to Support Artemis: The Apollo Records Synthesis Project

With the first crewed missions of the Artemis Program on the horizon, including the return of humans to another planetary surface, the space medicine and research communities have a renewed interest in buying down risk on these missions using historic Apollo datasets. Archivists with NASA’s Life Sciences Data Archive (LSDA) and epidemiologists with the Lifetime Surveillance of Astronaut Health (LSAH) are collaborating on a project aiming at improving access to historic datasets from the Apollo Program. The Apollo Records Synthesis Project (ARSP) seeks to expand the available historic biomedical knowledge base by examining physical records located across a wide range of collections, including examples such as pre-flight and post-flight physicals, lab reports, and handwritten flight surgeon and biomedical engineer logs from Apollo missions. The ARSP team has been able to identify several previously undocumented sources of biomedical information from Apollo missions. In the future, the team will modernize record storage and accessibility of these resources using digitization and natural language processing. This poster will discuss the progress of the project, give context to the dual research-clinical care nature of the records, and highlight the challenges and opportunities in using data from historical records. This poster will also provide information on how researchers can request access to datasets from these records.

life sciences↗

Rediscovering Apollo Biomedical Data to Support Artemis: The Apollo Records Synthesis Project

With the first crewed missions of the Artemis Program on the horizon, including the return of humans to another planetary surface, the space medicine and research communities have a renewed interest in buying down risk on these missions using historic Apollo datasets. Archivists with NASA’s Life Sciences Data Archive (LSDA) and epidemiologists with the Lifetime Surveillance of Astronaut Health (LSAH) are collaborating on a project aiming at improving access to historic datasets from the Apollo Program. The Apollo Records Synthesis Project (ARSP) seeks to expand the available historic biomedical knowledge base by examining physical records located across a wide range of collections, including examples such as pre-flight and post-flight physicals, lab reports, and handwritten flight surgeon and biomedical engineer logs from Apollo missions. The ARSP team has been able to identify several previously undocumented sources of biomedical information from Apollo missions. In the future, the team will modernize record storage and accessibility of these resources using digitization and natural language processing. This poster will discuss the progress of the project, give context to the dual research-clinical care nature of the records, and highlight the challenges and opportunities in using data from historical records. This poster will also provide information on how researchers can request access to datasets from these records.

life sciences↗

Wireless power transfer to biomedical implants

Various examples are provided for wireless power transfer to implants. In one example, a system includes a radio frequency (RF) power source and a transmitter (TX) array comprising an excitation coil and resonant coils distributed about the excitation coil. The TX array can transfer power from the RF power source to a biomedical implant inserted below a skin surface of a subject when the TX array is positioned on the skin surface adjacent to the biomedical implant. A receiver (RX) coil of the biomedical implant can inductively couple with the TX array for the power. The resonant coils can allow power transfer when the RX coil is not aligned with the excitation coil.

Lin, Jenshan↗

Wireless power transfer to biomedical implants

Various examples are provided for wireless power transfer to implants. In one example, a system includes a radio frequency (RF) power source and a transmitter (TX) array comprising an excitation coil and resonant coils distributed about the excitation coil. The TX array can transfer power from the RF power source to a biomedical implant inserted below a skin surface of a subject when the TX array is positioned on the skin surface adjacent to the biomedical implant. A receiver (RX) coil of the biomedical implant can inductively couple with the TX array for the power transfer. The resonant coils can allow power transfer when the RX coil is not aligned with the excitation coil.

Lin, Jenshan↗

Enabling end-to-end secure federated learning in biomedical research on heterogeneous computing environments with APPFLx

Facilitating large-scale, cross-institutional collaboration in biomedical machine learning (ML) projects requires a trustworthy and resilient federated learning (FL) environment to ensure that sensitive information such as protected health information is kept confidential. Specifically designed for this purpose, this work introduces APPFLx - a low-code, easy-to-use FL framework that enables easy setup, configuration, and running of FL experiments. APPFLx removes administrative boundaries of research organizations and healthcare systems while providing secure end-to-end communication, privacy-preserving functionality, and identity management. Furthermore, it is completely agnostic to the underlying computational infrastructure of participating clients, allowing an instantaneous deployment of this framework into existing computing infrastructures. Experimentally, the utility of APPFLx is demonstrated in two case studies: (1) predicting participant age from electrocardiogram (ECG) waveforms, and (2) detecting COVID-19 disease from chest radiographs. Here, ML models were securely trained across heterogeneous computing resources, including a combination of on-premise high-performance computing and cloud computing facilities. By securely unlocking data from multiple sources for training without directly sharing it, these FL models enhance generalizability and performance compared to centralized training models while ensuring data remains protected. In conclusion, APPFLx demonstrated itself as an easy-to-use framework for accelerating biomedical studies across organizations and healthcare systems on large datasets while maintaining the protection of private medical data.

Biomedical Research↗

Simulation of nonlinear propagation of biomedical ultrasound using PZFlex and the KZK Texas code

In biomedical ultrasound nonlinear acoustics can be important in both diagnostic and therapeutic applications and robust simulations tools are needed in the design process but also for day-to-day use such as treatment planning. For most biomedical application the ultrasound sources generate focused sound beams of finite amplitude. The KZK equation is a common model as it accounts for nonlinearity, absorption and paraxial diffraction and there are a number of solvers available, primarily developed by research groups. We compare the predictions of the KZK Texas code (a finite-difference time-domain algorithm) to an FEM-based commercial software, PZFlex. PZFlex solves the continuity equation and momentum conservation equation with a correction for nonlinearity in the equation of state incorporated using an incrementally linear, 2nd order accurate, explicit algorithm in time domain. Nonlinear ultrasound beams from two transducers driven at 1 MHz and 3.3 MHz respectively were simulated by both the KZK Texas code and PZFlex, and the pressure field was also measured by a fibre-optic hydrophone to validate the models. Further simulations were carried out a wide range of frequencies. The comparisons showed good agreement for the fundamental frequency for PZFlex, the KZK Texas code and the experiments. For the harmonic components, the KZK Texas code was in good agreement with measurements but PZFlex underestimated the amplitude: 32% for the 2nd harmonic and 66% for the 3rd harmonic. The underestimation of harmonics by PZFlex was more significant when the fundamental frequency increased. Furthermore non-physical oscillations in the axial profile of harmonics occurred in the PZFlex results when the amplitudes were relatively low. These results suggest that careful benchmarking of nonlinear simulations is important.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Conformal image-guided microbeam radiation therapy at the ESRF biomedical beamline ID17

Purpose: Upcoming veterinary trials in microbeam radiation therapy (MRT) demand for more advanced irradiation techniques than in preclinical research with small animals. The treatment of deep-seated tumors in cats and dogs with MRT requires sophisticated irradiation geometries from multiple ports, which impose further efforts to spare the normal tissue surrounding the target. Methods: This work presents the development and benchmarking of a precise patient alignment protocol for MRT at the biomedical beamline ID17 of the European Synchrotron Radiation Facility (ESRF). The positioning of the patient prior to irradiation is verified by taking x-ray projection images from different angles. Results: Using four external fiducial markers of 1.7 mm diameter and computed tomography-based treatment planning, a target alignment error of less than 2 mm can be achieved with an angular deviation of less than 2{sup ∘}. Minor improvements on the protocol and the use of smaller markers indicate that even a precision better than 1 mm is technically feasible. Detailed investigations concerning the imaging dose lead to the conclusion that doses for skull radiographs lie in the same range as dose reference levels for human head radiographs. A currently used online dose monitor for MRT has been proven to give reliable results for the imaging beam. Conclusions: The ESRF biomedical beamline ID17 is technically ready to apply conformal image-guided MRT from multiple ports to large animals during future veterinary trials.

60 APPLIED LIFE SCIENCES↗

The NASA Open Science Data Repository: Biomedical Fair Data, Analysis Tools, User Communities, Publications, and Discoveries for Deep Space Missions

Increased biomedical risks and challenges associated with deep space missions require new knowledge discovery, new health countermeasures, and development of novel ecosystems, life support, crop production, and biomedical support capabilities. To meet NASA’s Moon to Mars strategic program goals for Human and Biological Sciences, findable, accessible, interoperable, reusable (FAIR), and maximally open-access data is going to be required to enable humanity to thrive in deep space. Indeed, this cornerstone perspective on FAIR and maximally open access data was also recommended in the recent 2023-2032 Decadal Survey from the National Academies of Sciences, Engineering, and Medicine. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database, and meets various scientific, technical, and operational spaceflight needs. It offers public users and submitters the ability to upload, download, search, share, analyze, and visualize data across ‘omics, physiological, phenotypic, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive, and the NASA Biological Institutional Scientific Collection. OSDR has >455 studies with datasets from model organisms and non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets have raw FASTQ and FASTA files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) which was developed based on industry norms. OSDR also recently began a collaboration with the European Space Agency (ESA) to scientifically curate and make available >200 terabytes of human and model organism space-relevant data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics assay data types, and ~50 physiological-phenotypic-imaging assay data types, spanning ultrasonography, micro-computed tomography, histology, morphometric photography, rebound tonometry, gait analysis, optical coherence tomography, novel object recognition, flow cytometry, and immunohistochemistry. A suite of analysis tools are available for OSDR users including: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, which compiles radiation measurements relevant to human spaceflight and provides tools for accessing and manipulating the data, and 3) a Multi-study visualization tool which enables users to look across and combine GeneLab’s omics datasets across different experiments and missions. There are ~600 volunteer OSDR Analysis Working Group (AWG) members who: 1) provide feedback on scientific standards for reuse (subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability), and 2) collaborate to mine-reuse OSDR data conducting scientific analysis. OSDR has enabled 60 publications as of September 2023, many directly from AWG collaborations most notably the Cell Press package in 2020. Lastly, there are at least 15 articles which mine OSDR data part of a package of ~50 articles across Nature Portfolio with research stemming from I4, the Japan Aerospace Exploration Agency, NASA Space Biology, and the NASA Human Research Program.

space biology↗