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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Explainable Artificial Intelligence in Endocrinological Medical Research

Artificial Intelligence (AI) has been a part of the medical community for decades in the form of Clinical Decision Support Systems (CDSS) to aide physicians in diagnosis and categorization of patients (1). Recent years have seen a shift from expert-derived models to the integration of machine learning (ML) algorithms to drive the output of these AI systems due to the ability of ML models to more accurately make predictions by exploiting higher dimensional and often complex data. In many cases ML models gain their advantage in accuracy by capture complex and often non-linear relationships between features being used to make the prediction. However, the hype and excitement around these methods are tempered by the clinical utility of often black-box solutions driven by skepticism of results that are difficult for practitioners to not only interpret but explain to their patients (1-3). This skepticism is not unfounded as multiple examples of black-box solutions identifying incidental correlates as the key predictors have highlighted the potential bias in a training set, or reward system, that a ML model may exploit; for example a model discerning wolves from huskies based on snow in the background rather than features of the dogs (1, 4, 5).

Endocrinological, artificial intelligence, diabete↗
DOE OSTI2023

Unraveling Vulnerabilities in Endocrine Therapy-Resistant HER2+/ER+ Breast Cancer

Abstract Breast tumors overexpressing human epidermal growth factor receptor (HER2) confer intrinsic resistance to endocrine therapy (ET), and patients with HER2/estrogen receptor–positive (HER2+/ER+) breast cancer (BCa) are less responsive to ET than HER2–/ER+. However, real-world evidence reveals that a large subset of patients with HER2+/ER+ receive ET as monotherapy, positioning this treatment pattern as a clinical challenge. In the present study, we developed and characterized 2 in vitro models of ET-resistant (ETR) HER2+/ER+ BCa to identify possible therapeutic vulnerabilities. To mimic ETR to aromatase inhibitors (AIs), we developed 2 long-term estrogen deprivation (LTED) cell lines from BT-474 (BT474) and MDA-MB-361 (MM361). Growth assays, PAM50 subtyping, and genomic and transcriptomic analyses, followed by validation and functional studies, were used to identify targetable differences between ET-responsive parental and ETR-LTED HER2+/ER+ cells. Compared to their parental cells, MM361 LTEDs grew faster, lost ER, and increased HER2 expression, whereas BT474 LTEDs grew slower and maintained ER and HER2 expression. Both LTED variants had reduced responsiveness to fulvestrant. Whole-genome sequencing of aggressive MM361 LTEDs identified mutations in genes encoding transcription factors and chromatin modifiers. Single-cell RNA sequencing demonstrated a shift towards non-luminal phenotypes, and revealed metabolic remodeling of MM361 LTEDs, with upregulated lipid metabolism and ferroptosis-associated antioxidant genes, including GPX4. Combining a GPX4 inhibitor with anti-HER2 agents induced significant cell death in both MM361 and BT474 LTEDs. The BT474 and MM361 AI-resistant models capture distinct phenotypes of HER2+/ER+ BCa and identify altered lipid metabolism and ferroptosis remodeling as vulnerabilities of this type of ETR BCa.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Towards modeling phage therapy

Patients infected with life-threatening multi-drug resistant (MDR) bacteria have been treated with cocktails of bacteriophages. This is a complicated form of personalized medicine as the phages given to a patient have to be selected beforehand on the basis of their lytic capacity of the infecting bacteria. Because bacteria rapidly become resistant, the evolution of resistance to a diverse cocktail of phages is a complicated dynamical process, during which competing bacterial strains replace one another by accumulating several resistance mechanisms, each of which may involve a fitness cost. As a consequence, it is typically not known why a particular phage therapy succeeded or failed, and how one can optimize the composition of the cocktails to maximize the rate of success. To improve upon this, we extend an existing in vivo -calibrated mouse model into a novel mathematical model for the human situation, and include multiple phages infecting multiple bacterial strains, differing in their resistance to each of the phages. We adjust several parameter estimates of the bacterial model to the human situation, and use the model to describe a successful case of phage therapy involving several cocktails, each containing several phages. In the model, treatment success crucially depended on pretreatment resistance levels, and on the diversity and the timing of the cocktails. Once an appropriate cocktail is found, it is less important to further optimize the infection rates of the phages. Resistant bacterial strains expand rapidly when sensitive strains decline, and the higher the infectivity of the phages, the faster resistant strains expand. Because resistance evolves rapidly, it is best to provide a diverse set of phages right from the start of therapy, i.e., to hit hard and early, and create a high genetic barrier to bacterial resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

yippee like 3 (ypel3) is a novel gene required for myelinating and perineurial glia development

Hypomyelination, a neurological disorder characterized by a decrease in the production of myelin sheets by glial cells, often has no known etiology. Elucidating the genetic causes of hypomyelination provides a better understanding of myelination, as well as means to diagnose, council, and treat patients. Here, we present evidence that YIPPEE LIKE 3 (YPEL3), a gene whose developmental role was previously unknown, is required for central and peripheral glial cell development. We identified a child with a constellation of clinical features including cerebral hypomyelination, abnormal peripheral nerve conduction, hypotonia, areflexia, and hypertrophic peripheral nerves. Exome and genome sequencing revealed a de novo mutation that creates a frameshift in the open reading frame of YPEL3 , leading to an early stop codon. We used zebrafish as a model system to validate that YPEL3 mutations are causative of neuropathy. We found that ypel3 isexpressed in the zebrafish central and peripheral nervous system. Using CRISPR/Cas9 technology, we created zebrafish mutants carrying a genomic lesion similar to that of the patient. Our analysis revealed that Ypel3 is required for specification and migration of myelinating oligodendrocytes, timely exit of the perineurial glial precursors from the central nervous system (CNS), formation of the perineurium, and Schwann cell maturation. Consistent with these observations, zebrafish ypel3 mutants have metabolomic signatures characteristic of oligodendrocyte and Schwann cell differentiation defects, show decreased levels of Myelin basic protein in the central and peripheral nervous system, and develop defasciculated peripheral nerves. Locomotion defects were observed in adult zebrafish ypel3 mutants. These studies demonstrate that Ypel3 is a novel gene required for perineurial cell differentiation and glial myelination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A cell-based Papain-like Protease (PLpro) activity assay for rapid detection of active SARS-CoV-2 infections and antivirals

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants are a continuous threat to human life. An urgent need remains for simple and fast tests that reliably detect active infections with SARS-CoV-2 and its variants in the early stage of infection. Here we introduce a simple and rapid activity-based diagnostic (ABDx) test that identifies SARS-CoV-2 infections by measuring the activity of a viral enzyme, Papain-Like protease (PLpro). The test system consists of a peptide that fluoresces when cleaved by SARS PLpro that is active in crude, unprocessed lysates from human tongue scrapes and saliva. Test results are obtained in 30 minutes or less using widely available fluorescence plate readers, or a battery-operated portable instrument for on-site testing. Proof-of-concept was obtained in a study on clinical specimens collected from patients with COVID-19 like symptoms who tested positive (n = 10) or negative (n = 10) with LIAT RT-PCR using nasal mid turbinate swabs. When saliva from these patients was tested with in-house endpoint RT-PCR, 17 were positive and only 5 specimens were negative, of which 2 became positive when tested 5 days later. PLpro activity correlated in 17 of these cases (3 out of 3 negatives and 14 out of 16 positives, with one invalid specimen). Despite the small number of samples, the agreement was significant (p value = 0.01). Two false negatives were detected, one from a sample with a late Ct value of 35 in diagnostic RT-PCR, indicating that an active infection was no longer present. The PLpro assay is easily scalable and expected to detect all viable SARS-CoV-2 variants, making it attractive as a screening and surveillance tool. Additionally, we show feasibility of the platform as a new homogeneous phenotypic assay for rapid screening of SARS-CoV-2 antiviral drugs and neutralizing antibodies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Using intrahost single nucleotide variant data to predict SARS-CoV-2 detection cycle threshold values

Over the last four years, each successive wave of the COVID-19 pandemic has been caused by variants with mutations that improve the transmissibility of the virus. Despite this, we still lack tools for predicting clinically important features of the virus. In this study, we show that it is possible to predict the PCR cycle threshold (Ct) values from clinical detection assays using sequence data. Ct values often correspond with patient viral load and the epidemiological trajectory of the pandemic. Using a collection of 36,335 high quality genomes, we built models from SARS-CoV-2 intrahost single nucleotide variant (iSNV) data, computing XGBoost models from the frequencies of A, T, G, C, insertions, and deletions at each position relative to the Wuhan-Hu-1 reference genome. Our best model had an R 2 of 0.604 [0.593–0.616, 95% confidence interval] and a Root Mean Square Error (RMSE) of 5.247 [5.156–5.337], demonstrating modest predictive power. Overall, we show that the results are stable relative to an external holdout set of genomes selected from SRA and are robust to patient status and the detection instruments that were used. This study highlights the importance of developing modeling strategies that can be applied to publicly available genome sequence data for use in disease prevention and control.

COVID19↗
DOE OSTI2025

Sequencing and analysis of 131 SARS-CoV-2 isolates in previously sampled and unsampled regions of Jordan from 2020 to 2023

The Hashemite Kingdom of Jordan remains an understudied country for next generation sequencing analysis of SARS-CoV-2 genomes collected during the 2019 pandemic. Here we provide 131 additional reference genomes collected between 2020–2023 from SARS-CoV-2-positive patients across Jordan. Phylogenetic analysis supports existing pandemic narratives of changing clade dominance over time and adds genomes in novel Jordanian locations and timepoints to make Jordan SARS-CoV-2 databases more comprehensive. Samples from the less-sequenced cities of Ajloun, Jaresh, Karak, and Madaba identified previously unreported lineages while Amman, Irbid, and Zarqa have existing sequencing efforts bolstered. Despite many incomplete patient records and a relatively small sample size, we observe interesting symptom patterns that support existing global and Jordanian pandemic narratives. We note how in-country COVID-19 pandemic genomic studies showcase Jordan’s efforts to expand next generation sequencing capabilities, especially through the leveraging of EDGE COVID-19, a bioinformatics platform for performing rapid, batched analysis of SARS-CoV-2 sequencing that streamlines sample processing prepared from a network of hospital locations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Modeling the emergence of viral resistance for SARS-CoV-2 during treatment with an anti-spike monoclonal antibody

To mitigate the loss of lives during the COVID-19 pandemic, emergency use authorization was given to several anti-SARS-CoV-2 monoclonal antibody (mAb) therapies for the treatment of mild-to-moderate COVID-19 in patients with a high risk of progressing to severe disease. Monoclonal antibodies used to treat SARS-CoV-2 target the spike protein of the virus and block its ability to enter and infect target cells. Monoclonal antibody therapy can thus accelerate the decline in viral load and lower hospitalization rates among high-risk patients with variants susceptible to mAb therapy. However, viral resistance has been observed, in some cases leading to a transient viral rebound that can be as large as 3–4 orders of magnitude. As mAbs represent a proven treatment choice for SARS-CoV-2 and other viral infections, evaluation of treatment-emergent mAb resistance can help uncover underlying pathobiology of SARS-CoV-2 infection and may also help in the development of the next generation of mAb therapies. Although resistance can be expected, the large rebounds observed are much more difficult to explain. We hypothesize replenishment of target cells is necessary to generate the high transient viral rebound. Thus, we formulated two models with different mechanisms for target cell replenishment (homeostatic proliferation and return from an innate immune response antiviral state) and fit them to data from persons with SARS-CoV-2 treated with a mAb. We showed that both models can explain the emergence of resistant virus associated with high transient viral rebounds. We found that variations in the target cell supply rate and adaptive immunity parameters have a strong impact on the magnitude or observability of the viral rebound associated with the emergence of resistant virus. Both variations in target cell supply rate and adaptive immunity parameters may explain why only some individuals develop observable transient resistant viral rebound. Our study highlights the conditions that can lead to resistance and subsequent viral rebound in mAb treatments during acute infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Protein Factory on a Chip for Rapid Therapeutics

The potential for new, re-emerging, or engineered pandemic threats could challenge our nation's biosecurity, requiring rapid and flexible countermeasure development platforms. In healthcare, one of the main hindrances to the timely development of protein-based therapeutics for cancer, infectious disease, and other diseases has been a slow and expensive quality-controlled production stage. We present a protein-based technology that has the potential to address these crucial problems in biosecurity and healthcare by maximizing protein production and system portability, while minimizing production latency and cost. Specifically, we have developed a reusable, portable first-generation platform that leverages the advantages of cell-free protein synthesis (CFPS) and flow cells to create practical amounts of clinically relevant therapeutics. We have demonstrated that this technology is reusable and programmable, enabling a single platform that can synthesize multiple dosages of various therapeutics and vaccine in the field. Implementing this technology could mitigate pandemic threats by providing a rapidly-deployable (just-in-time), versatile (precision medicine) production of biologic therapeutics to the infected patient’s locale (point-of-care). In drug development, once promising drug variations are identified, the platform can be scaled to quickly produce practical amounts of protein for patient testing in the matter of days (vs. months) at a fraction of the cost of existing technology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Design Optimization of A generic Fissile Solution for Mo99 production using Electron Beam-based Neutron Generator using MCNP+CFD

Molybdenum-99 ( 99 Mo) is a medical isotope used in 80% of all medical imaging procedures today. However, 99 Mo is not directly administered to patients for imaging; its decay product, technetium-99m ( 99 mTc), is a metastable isotope with a half-life of ~6 hours. Such a short half-life does not allow for production, separation, and application to a patient before decaying further. Therefore, the solution is to produce the precursor to 99 mTc, 99 Mo. 99 Mo has a half-life of 66 hours, long enough to produce the material and send it to the desired location before it fully decays. Under National Nuclear Security Administration’s (NNSA) highly enriched uranium (HEU) minimization mission, the Material Management and Minimization (M3) office leads the Molybdenum-99 (Mo-99) program. A major goal of the Mo-99 program is to develop methods of producing 99 Mo using low enriched uranium (LEU) opposed to the traditionally used HEU domestically in the U.S. Internationally, LEU is the new standard for use in research reactors and isotope production facility. In this study, we introduce a generic fissile solution system for 99 Mo production facility meeting the design requirement of 1) LEU usage as fissile material and 2) subcritical fissile system coupled with a horizontal electron beam (E-beam) accelerator. The focus of this research is to optimize a fissile solution configuration for maximum 99 Mo production yield using MCNP model, and ultimately implement the optimized design with computational fluid dynamics (CFD) model to understand thermal hydraulic behavior and solution convection characteristic. The report consists of two parts: 1) isotope yield calculation and criticality analysis with a wide range of parametric test matrix, and 2) thermal hydraulic analysis for solution mixing and cooling assessment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Designing a dynamic vulnerability index to COVID-19 for New Mexico, USA

Motivation: Non-congregational shelters are a place where COVID-19 patients can quarantine away from their household until recovered. NM wants to establish non-congregational shelters for COVID-19 patients and first responders; Where? How many rooms? Create a decision support tool to assess which counties have the most vulnerable population to COVID-19; Socioeconomic status, community practices.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

CPAP Ventilators Needed for Rapid Response to COVID-19 by Modification of CPAP Equipment

Early on in the COVID-19 pandemic, potential ventilator shortages were a critical issue identified by national health care providers. Capacity modeling at the time suggested patient demand may exceed ventilator supply. Thus, the challenge became finding an urgent interim solution to meet health care needs. Our initial hypothesis was that CPAP technology could be modified to provide similar functionality to a ventilator, relieving demand and allowing physicians to decide which patients need high end machines, ultimately saving lives. In conjunction with medical experts and pulmonologists, we were able to identify three key thrusts associated with this research problem: (1) modification of CPAP technology to allow for 02 input that would be capable of providing ventilation; (2) development of an alarming function that would provide real-time audible alarms to alert medical personnel to critical conditions, which would be used inline with CPAP technology; and (3) a method of sterilizing expiratory air from such a system in order to protect medical personnel from biohazard, since CPAPs vent to the atmosphere. We were unable to realize results for thrust 1 (CPAP modification for 02); we identified potential safety issues associated with utilizing medical grade oxygen with a common CPAP device. In order to characterize and mitigate these issues, we would need to partner closely with a device manufacturer; such a partnership could not be achieved in the timeframe needed for this rapid response work. However, we determined that some medical grade BiPAP devices do not need this modification and that the significant progress on thrusts 2 and 3 would be sufficient to buy down risk of a massive ventilator shortage. Our team built a prototype alarm system that can be utilized with any assistive respiratory device to alert on all key conditions identified by medical personnel (high pressure, low pressure, apnea, loss of power, low battery). Finally, our team made significant progress in the rapid prototyping and demonstration of an inline UV air purifier device. The device is cost efficient and can be manufactured at scale with both commercially available and additively manufactured parts. Initial tests with SARS-CoV-2 analog bacteriophage MS2 show 99% efficacy at reducing bioburden. Following a successful demonstration of the prototype device with medical personnel, we were able to obtain follow-on (non-LDRD) funding to provide additional device characterization, validation, and production in order to respond to an immediate regional need.

42 ENGINEERING↗
DOE OSTI2020

Cooperative Research and Development Agreement With Georgetown University Report: National Institutes of Health, National Center for Advancing Translational Sciences Clinical and Translational Science Award

Oak Ridge National Laboratory (ORNL) is participating with Georgetown University (GU) as a subrecipient in response to the National Institutes of Health (NIH), National Center for Advancing Translational Sciences (NCATS) Clinical and Translational Science Award (CTSA) (U54 Clinical Trial Optional) funding opportunity announcement. This Cooperative Research and Development Agreement is put in to place to facilitate the development and implementation of clinical interventions that demonstrably improve human health is currently a complex, recursive, and inefficient process that leads to delays of years or decades before discoveries in biomedical research result in health benefits for patients and communities. NCATS conducts and supports research in the science of translation, to discover the mechanistic and operational principles of the intervention development and dissemination process, thereby providing the scientific foundation for improvements in translational efficiency that will accelerate the realization of interventions that improve human health. Under NCATS’ leadership, the CTSA Program supports a national network of medical research institutions called hubs. GU is the lead institution in one of the NIH hubs that was created as a result of a previous NIH CTSA. The missions of the GU have historically included the advancement of health through research in the clinical and biomedical sciences, the education of future leaders in medical and nursing practice and academia, and the provision of compassionate and scientifically competent patient care and service to the Washington, DC community and the nation. GU is the lead institution for the Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS), a multi-institutional partnership of medical research institutions forged from a desire to promote clinical research and translational science. Through multiple collaborations among these institutions, GHUCCTS is transforming clinical research and translational science in order to bring new scientific advances to health care. Oak Ridge National Laboratory is the Department of Energy's (DOE) largest science and energy laboratory. Managed since April 2000 by a partnership of the University of Tennessee and Battelle, ORNL was established in 1943 as a part of the secret Manhattan Project to pioneer a method for producing and separating plutonium. During the 1950s and 1960s, ORNL became an international center for the study of nuclear energy and related research in the physical and life sciences. With the creation of DOE in the 1970s, ORNL's mission broadened to include a variety of energy technologies and strategies. Today the laboratory supports the nation with a peacetime science and technology mission that is just as important as, but very different from, its role during the Manhattan Project. ORNL is home to the world's premier center for high performance supercomputing to enable scientific discovery. ORNL has extensive expertise in various areas of computer science that are uniquely situated to support GU. Additionally, ORNL’s leading computational user facilities present a unique opportunity to leverage the largest scale machines for open science in support of the stated mission of the NCATS CTSA. ORNL's partnership with GU will offer unparalleled opportunity in data analytics, deep-learning, artificial intelligence, and urban dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Uncertainty Analysis Framework for the Hospital Resource Supply Model for Covid-19

In March and April of 2020 there was widespread concern about availability of medical resources required to treat Covid-19 patients who become seriously ill. A simulation model of supply management was developed to aid understanding of how to best manage available supplies and channel new production. Forecasted demands for critical therapeutic resources have tremendous uncertainty, largely due to uncertainties about the number and timing of patient arrivals. It is therefore essential to evaluate any process for managing supplies in view of this uncertainty. To support such evaluations, we developed a modeling framework that would allow an integrated assessment in the context of uncertainty quantification. At the time of writing there has been no need to execute this framework because adaptations of the medical system have been able to respond effectively to the outbreak. This report documents the framework and its implemented components should need later arise for its application.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Health Hazards of Exposures to Radioiodine

Iodine is a chemical element with atomic number 53. Iodine-127 is stable (non-radioactive) and commonly found in nature. Elemental iodine is a purple-colored solid at room temperature and pressure, but spontaneously sublimates (turns into vapor). Iodine is an essential element for life, and is required for proper functioning of the thyroid. Iodine is present in many foods, and is readily absorbed by the body and concentrated in the thyroid gland. A fraction of iodine ingested or inhaled is rapidly removed by the kidneys. The rest of the inhaled or ingested iodine is absorbed the by thyroid and retained for many months. Iodine has a biological half-life of approximately 120 days in health individuals. The biological half-life can be shorter in individuals with hyperthyroidism, and longer in individuals with hypothyroidism. Iodine has a number of radioactive isotopes, most of which have relatively short half-lives (days or weeks). Short half-life iodine isotopes are useful for a variety of medical applications, including imaging and cancer therapy. For example, Iodine-123 (half-life 13 hours) is commonly used for medical imaging of the thyroid, while iodine-131 (half-life 8 days) is used for suppressing thyroid function in individuals with hyperthyroidism or ablating (killing) thyroid cells to treat thyroid cancer. Iodine-125 (half-life 59 days) is produced in nuclear reactors, and has medical uses. Although iodine-125 can be used for thyroid imaging, Iodine-123 is more commonly used for that purpose because of its shorter half-life and higher-energy emissions. Iodine-125 is more commonly used for cancer treatment, and can be processed into small metal pellets (seeds) inserted directly into a tumor. Iodine-125 emits low-energy x-rays which can kill tumor cells and generally cannot escape the tumor, sparing other tissues. Medical iodine for imaging or treatment is typically administered orally in the form a pill or liquid solution. A typical adult thyroid scan using iodine-123 involves having the patient swallow between one and four 0.1 millicuries pills, with the exact dose dependent on the patient’s weight. This results in a whole-body committed effective dose of 80 – 320 mrem, and a thyroid equivalent dose of 1443 – 5772 mrem. Note that the whole-body effective dose relates to the overall cancer risk, while the larger equivalent dose to the thyroid only indicates that most of this risk is the result of exposure to the thyroid. These doses are considered safe, although the procedure is not recommended for pregnant or breastfeeding women. In contrast, the quantities of iodine-131 used for treatment of hyperthyroidism and thyroid cancers are much higher. For treatment of hyperthyroidism, 4 – 10 millicuries are administered, while for thyroid cancer the administration can range from 50 – 150 millicuries of I-131. In addition to medical exposures, large populations were exposed to radioiodine as result of the atomic bombings of Hiroshima and Nagasaki in Japan, and the Chernobyl nuclear accident. These populations have been carefully followed for many years to assess the effect of their radiation exposures on cancer risk. As a result, a great deal is known about the cancer risks associated with radioiodine exposure. Because iodine is concentrated in the thyroid, the principal risk of exposure to radioiodine is thyroid cancer. Children have the highest risk of thyroid cancer after exposure to radioactive iodine. According to a large study of Japanese atomic bomb survivors, an effective dose of one Sievert (100,000 mrem) has been observed to increase the risk of thyroid cancer by a factor of 9.5 in children aged zero to nine years old, by a factor of 3 in children aged 10 to 19 years old, and by barely detectable amounts in adults. Another way of quantifying the risk from radioiodine exposure is from risk coefficients, which provide the risk per unit intake of radionuclides in terms of both morbidity (any cancer) and mortality (death). Both morbidity (risk of cancer) and mortality (death) risks are shown in the table below. Note that because thyroid cancer is almost never fatal, the morbidity coefficients are much larger than the mortality coefficients.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

RCT Module 2.15 Radiological Considerations for First Aid [Presentation]

Standard first aid is applied before contamination control whenever it is considered to have life-saving value or is important to the patient for the relief of pain or prevention of disability. It is the obligation of all who assist a patient to render such aid within the limits of their training and qualifications.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Women in Data Science Livermore Datathon 2024

The WiDS Datathon 2024 focuses on a prediction task using a roughly 39k record dataset (split into training and test sets) representing patients and their characteristics (age, race, BMI, zip code), their diagnosis and treatment information (breast cancer diagnosis code, metastatic cancer diagnosis code, metastatic cancer treatments, … etc.), their geo (zip-code level) demographic data (income, education, rent, race, poverty, …etc), as well as toxic air quality data (Ozone, PM25 and NO2) that tie health outcomes to environmental conditions. Each row in the data corresponds a single patient and her Diagnosis Period.

59 BASIC BIOLOGICAL SCIENCES↗