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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Portable computing - A fielded interactive scientific application in a small off-the-shelf package

Experience with the design and implementation of a portable computing system for STS crew-conducted science is discussed. Principal-Investigator-in-a-Box (PI) will help the SLS-2 astronauts perform vestibular (human orientation system) experiments in flight. PI is an interactive system that provides data acquisition and analysis, experiment step rescheduling, and various other forms of reasoning to astronaut users. The hardware architecture of PI consists of a computer and an analog interface box. 'Off-the-shelf' equipment is employed in the system wherever possible in an effort to use widely available tools and then to add custom functionality and application codes to them. Other projects which can help prospective teams to learn more about portable computing in space are also discussed.

Groleau, Nicolas↗
NASA NTRS2015

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction can be used for more efficient runway scheduling to increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. This paper describes two different approaches to predicting taxi times, which are a data-driven analytical method using machine learning techniques and a fast-time simulation-based approach. These two taxi time prediction methods are applied to realistic flight data at Charlotte Douglas International Airport (CLT) and assessed with actual taxi time data from the human-in-the-loop simulation for CLT airport operations using various performance measurement metrics. Based on the preliminary results, we discuss how the taxi time prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast-time simulation model for implementing it with an airport scheduling algorithm in real-time operational environment.

Lee, Hanbong↗
NASA NTRS2019

Human Factors Applications of Biomechanical Modeling

Biomechanical data collection and modeling has applications to the field of human factors. Specifically, motion data can be used to determine the operational volume necessary for performing a task. The operational volume assessment can be performed in order to determine how much volume is needed to perform the task or if task performance can be contained and adequately performed within an allocated volume. Motion and external force data, along with computational modeling techniques, can be used to estimate the internal loading produced during performance of a task. Internal loading estimates can be used to determine if an adequate stimulus is generated for maintenance of musculoskeletal health and also for comparison to injury thresholds to determine injury risk during task performance.

Lewandowski, Beth↗
NASA NTRS2021

NASA Human Systems Integration Handbook

This handbook is intended to provide general guidance and information on Human Systems Integration (HSI) for the NASA community and the applicability of HSI to NASA programs and projects. The primary goals are to increase awareness and consistency across the Agency, advance the practice and implementation of HSI principles, and provide invaluable information and guidance to HSI practitioners in the performance of their duties. Specific aims of this handbook are to define HSI, illustrate the value of HSI in programmatic decisions, demonstrate how HSI fits into the NASA project life cycle process, describe how HSI applies across all three NASA Technical Authorities, provide guidance on HSI processes and products, and provide helpful information on HSI resources within the NASA community. Largely within the engineering community, a system is thought of as the integration or assemblance of hardware and software that together perform a function. HSI considers a system to be the integration of hardware, software, humans, data, and processes, where the human in HSI refers to all personnel involved with a given system, including system owners, users/customers, operators, maintainers, assemblers, support personnel, logistics suppliers, training personnel, test personnel, and others. This handbook should be used as a companion for implementing NPR 7123.1, Systems Engineering Processes and Requirements, the NASA Systems Engineering Handbook, NASA directives, and any Center-specific handbooks and directives developed for implementing programs and projects. As of 2021, both NPR 7123.1 and NPR 7120.5 require HSI to be implemented within NASA technical efforts.

Lisa O Rippy↗
NASA NTRS2012

Quantifying Pilot Visual Attention in Low Visibility Terminal Operations

Quantifying pilot visual behavior allows researchers to determine not only where a pilot is looking and when, but holds implications for specific behavioral tracking when these data are coupled with flight technical performance. Remote eye tracking systems have been integrated into simulators at NASA Langley with effectively no impact on the pilot environment. This paper discusses the installation and use of a remote eye tracking system. The data collection techniques from a complex human-in-the-loop (HITL) research experiment are discussed; especially, the data reduction algorithms and logic to transform raw eye tracking data into quantified visual behavior metrics, and analysis methods to interpret visual behavior. The findings suggest superior performance for Head-Up Display (HUD) and improved attentional behavior for Head-Down Display (HDD) implementations of Synthetic Vision System (SVS) technologies for low visibility terminal area operations. Keywords: eye tracking, flight deck, NextGen, human machine interface, aviation

Ellis, Kyle K.↗
NASA NTRSDate not supplied

Assessing Hot Fire Data with WinPlot

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health and performance pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

J. Davis Hunter↗
NASA NTRSDate not supplied

Applications and Performance of a Lightning Risk Assessment using Geostationary Lightning Mapper (GLM) Data

Lightning is a hazard globally, particularly in lesser-developed countries. Cloud-to-ground lightning strikes are a threat to human safety, motivating a desire to monitor location-based lightning risk to mitigate harm. A lightning risk assessment for human safety was created that uses a combination of probabilistic risk calculation and spatial lightning mapping data to produce a risk magnitude. This risk magnitude evolves with time and changing conditions and is compared to tolerability thresholds in order to evaluate safety. The risk assessment using lightning mapping array (LMA) flash extent density (FED) data was found to perform comparatively (with respect to issuing lightning warnings) to a more standard method of monitoring lightning safety where National Lightning Detection Network (NLDN) flashes were monitored within a 5 nautical mile radius of a location of interest. This research investigates the replacement of LMA FED with FED from the Geostationary Lightning Mapper (GLM) within the risk assessment framework. Using GLM FED would allow for risk to be calculated outside of LMA domains and anywhere within the GLM field of view, including areas outside of the United States (US). A few applications of the risk method with GLM FED are shown and discussed for locations both in and outside of the US. Additionally, the performance of the risk method is compared based on the type of lightning input source (LMA vs GLM). The end goal of this work is to provide forecasters and end users with a tool to help monitor lightning risk in decision support scenarios.

Kelley Murphy↗
DOE OSTI2015

A pilot study on the feasibility of European harmonized human biomonitoring: Strategies towards a common approach, challenges and opportunities

In 2004 the European Commission and Member States initiated activities towards a harmonized approach for Human Biomonitoring surveys throughout Europe. The main objective was to sustain environmental health policy by building a coherent and sustainable framework and by increasing the comparability of data across countries. A pilot study to test common guidelines for setting up surveys was considered a key step in this process. Through a bottom-up approach that included all stakeholders, a joint study protocol was elaborated. From September 2011 till February 2012, 17 European countries collected data from 1844 mother–child pairs in the frame of DEMOnstration of a study to COordinate and Perform Human Biomonitoring on a European Scale (DEMOCOPHES). Mercury in hair and urinary cadmium and cotinine were selected as biomarkers of exposure covered by sufficient analytical experience. Phthalate metabolites and Bisphenol A in urine were added to take into account increasing public and political awareness for emerging types of contaminants and to test less advanced markers/markers covered by less analytical experience. Extensive efforts towards chemo-analytical comparability were included. The pilot study showed that common approaches can be found in a context of considerable differences with respect to experience and expertize, socio-cultural background, economic situation and national priorities. It also evidenced that comparable Human Biomonitoring results can be obtained in such context. A European network was built, exchanging information, expertize and experiences, and providing training on all aspects of a survey. A key challenge was finding the right balance between a rigid structure allowing maximal comparability and a flexible approach increasing feasibility and capacity building. Next steps in European harmonization in Human Biomonitoring surveys include the establishment of a joint process for prioritization of substances to cover and biomarkers to develop, linking biomonitoring surveys with health examination surveys and with research, and coping with the diverse implementations of EU regulations and international guidelines with respect to ethics and privacy. - Highlights: • A common European Human Biomonitoring (HBM) survey protocol was developed through a bottom-up approach. • A joint process for prioritization was established to select a limited set of biomarkers, some covered by experience and others for emerging substances. • The protocol was tested in a pilot study, resulting in HBM results comparable on a European scale which sustained environmental health policy. • Ethics and privacy regulations were not an obstacle for transnational harmonization.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Medical Data Architecture Platform and Recommended Requirements for A Medical Data System for Exploration Missions

Minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm of medical data management on the International Space Station. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products derived from the third MDA prototype development will directly inform exploration medical system requirements for Level of Care IV in Gateway missions.In fiscal year 2019, the MDA project developed Test Bed 3, the third iteration in a series of prototypes, that featured integrations with cognition tool data, ultrasound image analytics and core Flight Software (cFS). Maintaining a layered architecture design, the framework implemented a plug-in, modular approach in the integration of these external data sources. An early version of MDA Test Bed 3 software was deployed and operated in a simulated analog environment that was part of the Next Space Technologies for Exploration Partnerships (NextSTEP) Gateway tests of multiple habitat prototypes. In addition, the MDA team participated in the Gateway Test and Verification Demonstration, where the MDA cFS applications was integrated with Gateway-in-a-Box software to send and receive medically relevant data over a simulated vehicle network. This software demonstration was given to ExMC and Gateway Program stakeholders at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Also, the integrated prototypes served as a vehicle to provide Level 5 requirements for the Crew Health and Performance Habitat Data System for Gateway Missions (Medical Level of Care IV). In the upcoming fiscal year, the MDA project will continue to provide systems engineering and vertical prototypes to refine requirements for medical Level of Care IV and inform requirements for Level of Care V.

Krihak, M.↗
NASA NTRS2011

Integration and Cooperation in the Next Golden Age of Human Space Flight Data Repositories: Tools for Retrospective Analysis and Future Planning

As NASA transitions from the Space Shuttle era into the next phase of space exploration, the need to ensure the capture, analysis, and application of its research and medical data is of greater urgency than at any other previous time. In this era of limited resources and challenging schedules, the Human Research Program (HRP) based at NASA s Johnson Space Center (JSC) recognizes the need to extract the greatest possible amount of information from the data already captured, as well as focus current and future research funding on addressing the HRP goal to provide human health and performance countermeasures, knowledge, technologies, and tools to enable safe, reliable, and productive human space exploration. To this end, the Science Management Office and the Medical Informatics and Health Care Systems Branch within the HRP and the Space Medicine Division have been working to make both research data and clinical data more accessible to the user community. The Life Sciences Data Archive (LSDA), the research repository housing data and information regarding the physiologic effects of microgravity, and the Lifetime Surveillance of Astronaut Health Repository (LSAH-R), the clinical repository housing astronaut data, have joined forces to achieve this goal. The task of both repositories is to acquire, preserve, and distribute data and information both within the NASA community and to the science community at large. This is accomplished via the LSDA s public website (http://lsda.jsc.nasa.gov), which allows access to experiment descriptions including hardware, datasets, key personnel, mission descriptions and a mechanism for researchers to request additional data, research and clinical, that is not accessible from the public website. This will result in making the work of NASA and its partners available to the wider sciences community, both domestic and international. The desired outcome is the use of these data for knowledge discovery, retrospective analysis, and planning of future research studies.

Thomas, D.↗
NASA NTRS2011

NASA Life Sciences Data Repositories: Tools for Retrospective Analysis and Future Planning

As NASA transitions from the Space Shuttle era into the next phase of space exploration, the need to ensure the capture, analysis, and application of its research and medical data is of greater urgency than at any other previous time. In this era of limited resources and challenging schedules, the Human Research Program (HRP) based at NASA s Johnson Space Center (JSC) recognizes the need to extract the greatest possible amount of information from the data already captured, as well as focus current and future research funding on addressing the HRP goal to provide human health and performance countermeasures, knowledge, technologies, and tools to enable safe, reliable, and productive human space exploration. To this end, the Science Management Office and the Medical Informatics and Health Care Systems Branch within the HRP and the Space Medicine Division have been working to make both research data and clinical data more accessible to the user community. The Life Sciences Data Archive (LSDA), the research repository housing data and information regarding the physiologic effects of microgravity, and the Lifetime Surveillance of Astronaut Health (LSAH-R), the clinical repository housing astronaut data, have joined forces to achieve this goal. The task of both repositories is to acquire, preserve, and distribute data and information both within the NASA community and to the science community at large. This is accomplished via the LSDA s public website (http://lsda.jsc.nasa.gov), which allows access to experiment descriptions including hardware, datasets, key personnel, mission descriptions and a mechanism for researchers to request additional data, research and clinical, that is not accessible from the public website. This will result in making the work of NASA and its partners available to the wider sciences community, both domestic and international. The desired outcome is the use of these data for knowledge discovery, retrospective analysis, and planning of future research studies.

Thomas, D.↗
DOE OSTI2024

CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal

In recent years, there has been a growing interest in profiling multiomic modalities within individual cells simultaneously. One such example is integrating combined single-cell RNA sequencing (scRNA-seq) data and single-cell transposase-accessible chromatin sequencing (scATAC-seq) data. Integrated analysis of diverse modalities has helped researchers make more accurate predictions and gain a more comprehensive understanding than with single-modality analysis. However, generating such multimodal data is technically challenging and expensive, leading to limited availability of single-cell co-assay data. Here, we propose a model for cross-modal prediction between the transcriptome and chromatin profiles in single cells. Our model is based on a deep neural network architecture that learns the latent representations from the source modality and then predicts the target modality. It demonstrates reliable performance in accurately translating between these modalities across multiple paired human scATAC-seq and scRNA-seq datasets. Additionally, we developed CrossMP, a web-based portal allowing researchers to upload their single-cell modality data through an interactive web interface and predict the other type of modality data, using high-performance computing resources plugged at the backend.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays

Recently, quantitative models based on signal detection theory have been successfully applied to the prediction of human accuracy in visual search for a target that differs from distractors along a single attribute (feature search). The present paper extends these models for visual search accuracy to multidimensional search displays in which the target differs from the distractors along more than one feature dimension (conjunction, disjunction, and triple conjunction displays). The model assumes that each element in the display elicits a noisy representation for each of the relevant feature dimensions. The observer combines the representations across feature dimensions to obtain a single decision variable, and the stimulus with the maximum value determines the response. The model accurately predicts human experimental data on visual search accuracy in conjunctions and disjunctions of contrast and orientation. The model accounts for performance degradation without resorting to a limited-capacity spatially localized and temporally serial mechanism by which to bind information across feature dimensions.

Non-NASA Center↗
DOE OSTI2019

Dose Calculation Methodology and Data for Solid Waste Performance Assessment and Composite Analysis at the Savannah River Site

This report provides a detailed description of the methodology developed to perform dose calculations for E-Area Low Level Waste Facility Performance Assessments and Savannah River Site Composite Analyses. Chapters 2 – 8 give a complete set of equations to be used to calculate dose for individual exposure pathways. The first set of dose scenarios assume that a member of the public establishes residence near the waste site and uses contaminated groundwater or contaminated surface water for personal consumption and to irrigate a garden and pasture where produce and farm animals are raised. Products from the garden and farm animals are used for personal consumption. This scenario applies to both E-Area Performance Assessments and Savannah River Site Composite Analyses. General dose exposure pathways for the resident farmer scenario are: 1. Ingestion pathways described in Chapter 2, 2. Inhalation pathways described in Chapter 3, 3. External exposure pathways described in Chapter 4, and 4. Recreational pathways described in Chapter 5 (Composite Analysis only). Doses from all of the above pathways are directly related to the contaminant concentration in the water. Additional dose scenarios considered for E-Area Performance Assessment assume that an inadvertent intruder encroaches on the waste disposal site after loss of institutional control. General dose exposure pathways considered for the inadvertent intruder are: 1. Ingestion pathways described in Chapter 6, 2. Inhalation pathways described in Chapter 7, and 3. External exposure pathways described in Chapter 8. Doses from all of the intruder pathways are directly related to the contaminant concentration in the buried waste. Special dose considerations related to human consumption of meat and dairy, and treatment of tritium in dose calculations are discussed in Chapter 9. Chapter 10 describes an Excel database named “Radionuclide, Element and Dose Parameter Data Package” that has been created to provide a system for maintaining the data required to perform radionuclide transport and dose calculations. This data includes: Isotope physical parameters and radioactive decay data needed for both transport and dose calculations, Isotope-specific dose coefficients and soil shielding factors associated with exposure pathways, Radionuclide drinking water concentration limits either published by the Environmental Protection Agency or derived from internal dose coefficients to meet the groundwater protection requirements in Department of Energy Order 435.1, Element-specific bio-transfer factors used in dose calculations, Dose equations and values of physical parameters and human factors used in dose calculations, and Key physical constants used in dose calculations. Revision 1 incorporates updated information developed since this report was issued for use in the next revision of the E-Area Low-Level Waste Facility Performance Assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Remote Sensor Design for Visual Recognition with Convolutional Neural Networks

While deep learning technologies for computer vision have developed rapidly since 2012, modeling of remote sensing systems has remained focused around human vision. In particular, remote sensing systems are usually constructed to optimize sensing cost-quality trade-offs with respect to human image interpretability. While some recent studies have explored remote sensing system design as a function of simple computer vision algorithm performance, there has been little work relating this design to the state-of-the-art in computer vision: deep learning with convolutional neural networks. We develop experimental systems to conduct this analysis, showing results with modern deep learning algorithms and recent overhead image data. Our results are compared to standard image quality measurements based on human visual perception, and we conclude not only that machine and human interpretability differ significantly, but that computer vision performance is largely self-consistent across a range of disparate conditions. This repository contains all the code required to replicate the results of our research paper, and the corresponding docker environment in which that code can be executed. All code is written in Python3 and utilizes the PyTorch library (v1.0) for neural network model training and evaluation. Jupyter notebooks are used to visualize images transformed with our code, in addition to plotting experimental results. We also include the specific parameter files used to execute our experiments, with the intent that these experiments can be replicated.

Zelinski, michaelE.↗
DOE OSTI2015

Enhanced DEA model with undesirable output and interval data for rice growing farmers performance assessment

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, this undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firms efficiency. Additionally, climatic factors as well as data uncertainty can significantly affect the efficiency analysis. There are a number of approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers has pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, it has been found that interval data approach is the most suitable to account for data uncertainty as it is much simpler to model and need less information regarding its distribution and membership function. In this paper, an enhanced DEA model based on DDF approach that considers undesirable outputs as well as climatic factors and interval data is proposed. This model will be used to determine the efficiency of rice farmers who produces undesirable outputs and operates under uncertainty. It is hoped that the proposed model will provide a better estimate of rice farmers’ efficiency.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Jong, Jen-Yi↗
DOE OSTI2015

Potential mechanisms for cancer resistance in elephants and comparative cellular response to DNA damage in humans

Here, evolutionary medicine may provide insights into human physiology and pathophysiology, including tumor biology. To identify mechanisms for cancer resistance in elephants and compare cellular response to DNA damage among elephants, healthy human controls, and cancer-prone patients with Li-Fraumeni syndrome (LFS). Design, Setting, and Participants A comprehensive survey of necropsy data was performed across 36 mammalian species to validate cancer resistance in large and long-lived organisms, including elephants (n=644). The African and Asian elephant genomes were analyzed for potential mechanisms of cancer resistance. Peripheral blood lymphocytes from elephants, healthy human controls, and patients with LFS were tested in vitro in the laboratory for DNA damage response. The study included African and Asian elephants (n=8), patients with LFS (n=10), and age-matched human controls (n=11). Human samples were collected at the University of Utah between June 2014 and July 2015. Exposures Ionizing radiation and doxorubicin. Cancer mortality across species was calculated and compared by body size and life span. The elephant genome was investigated for alterations in cancer-related genes. DNA repair and apoptosis were compared in elephant vs human peripheral blood lymphocytes. Across mammals, cancer mortality did not increase with body size and/or maximum life span (eg, for rock hyrax, 1% [95% CI, 0%-5%]; African wild dog, 8% [95% CI, 0%-16%]; lion, 2% [95% CI, 0%-7%]). Despite their large body size and long life span, elephants remain cancer resistant, with an estimated cancer mortality of 4.81% (95% CI, 3.14%-6.49%), compared with humans, who have 11% to 25% cancer mortality. While humans have 1 copy (2 alleles) of TP53, African elephants have at least 20 copies (40 alleles), including 19 retrogenes (38 alleles) with evidence of transcriptional activity measured by reverse transcription polymerase chain reaction. In response to DNA damage, elephant lymphocytes underwent p53-mediated apoptosis at higher rates than human lymphocytes proportional to TP53 status (ionizing radiation exposure: patients with LFS, 2.71% [95% CI, 1.93%-3.48%] vs human controls, 7.17% [95% CI, 5.91%-8.44%] vs elephants, 14.64% [95% CI, 10.91%-18.37%]; P<.001; doxorubicin exposure: human controls, 8.10% [95% CI, 6.55%-9.66%] vs elephants, 24.77% [95% CI, 23.0%-26.53%]; P<.001). Compared with other mammalian species, elephants appeared to have a lower-than-expected rate of cancer, potentially related to multiple copies of TP53. Compared with human cells, elephant cells demonstrated increased apoptotic response following DNA damage. These findings, if replicated, could represent an evolutionary-based approach for understanding mechanisms related to cancer suppression.

60 APPLIED LIFE SCIENCES↗