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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 37 records · Page 2

Molecular-Level Dysregulation of Insulin Pathways and Inflammatory Processes in Peripheral Blood Mononuclear Cells by Circadian Misalignment

Circadian misalignment due to night work has been associated with elevated risk for chronic diseases. Here, we investigated the effects of circadian misalignment using shotgun protein profiling of peripheral blood mononuclear cells taken from healthy humans during a constant routine protocol, which was conducted immediately after participants had been subjected to a 3-day simulated night shift schedule or a 3-day simulated day shift schedule. By comparing proteomic profiles between the simulated shift conditions, we identified proteins and pathways that are associated with the effects of circadian misalignment, and observed that insulin regulation pathways and inflammation-related proteins displayed markedly different temporal patterns after simulated night shift. Further, by integrating the proteomic profiles with previously assessed metabolomic profiles in a network-based approach, we found key associations between circadian dysregulation of protein-level pathways and metabolites of interest in the context of chronic metabolic diseases. Overall, our results suggest that circadian misalignment is associated with a tug of war between central clock mechanisms controlling insulin secretion and peripheral clock mechanisms regulating insulin sensitivity, which may lead to adverse long-term outcomes such as diabetes and obesity. Our study provides a molecular-level mechanism linking circadian misalignment and adverse long-term health consequences of night work.

59 BASIC BIOLOGICAL SCIENCES↗

Accelerated epigenetic aging as a risk factor for chronic obstructive pulmonary disease and decreased lung function in two prospective cohort studies

Chronic obstructive pulmonary disease (COPD) is a frequent diagnosis in older individuals and contributor to global morbidity and mortality. Given the link between lung disease and aging, we need to understand how molecular indicators of aging relate to lung function and disease. Using data from the population-based KORA (Cooperative Health Research in the Region of Augsburg) surveys, we associated baseline epigenetic (DNA methylation) age acceleration with incident COPD and lung function. Models were adjusted for age, sex, smoking, height, weight, and baseline lung disease as appropriate. Associations were replicated in the Normative Aging Study. Of 770 KORA participants, 131 developed incident COPD over 7 years. Baseline accelerated epigenetic aging was significantly associated with incident COPD. The change in age acceleration (follow-up – baseline) was more strongly associated with COPD than baseline aging alone. The association between the change in age acceleration between baseline and follow-up and incident COPD replicated in the Normative Aging Study. Associations with spirometric lung function parameters were weaker than those with COPD, but a meta-analysis of both cohorts provide suggestive evidence of associations. Accelerated epigenetic aging, both baseline measures and changes over time, may be a risk factor for COPD and reduced lung function.

60 APPLIED LIFE SCIENCES↗

Chronic obstructive pulmonary disease among former United States Department of Energy workers: comorbidities and lung function changes

Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality in the United States and is frequently associated with multiple comorbidities which lead to poor COPD outcomes in the general population. However, little is known regarding COPD comorbidities in occupational cohorts whose exposure experiences could result in differences in comorbidities compared to the general population. These differences may also be important for assessing COPD outcomes such as lung function changes or decline. Therefore, the objectives of this study were to: (1) identify and describe clusters of COPD comorbidities among Department of Energy (DOE) former workers; (2) assess if the attributes of the identified clusters differ from those identified among the general population based on the published literature, and (3) identify predictors of lung function changes and decline among DOE former workers.

60 APPLIED LIFE SCIENCES↗

In with the old, in with the new: machine learning for time to event biomedical research

The predictive modeling literature for biomedical applications is dominated by biostatistical methods for survival analysis, and more recently some out of the box machine learning approaches. In this article, we show a presentation of a machine learning method appropriate for time-to-event modeling in the area of prostate cancer long-term disease progression. Using XGBoost adapted to long-term disease progression, we developed a predictive model for 118 788 patients with localized prostate cancer at diagnosis from the Department of Veterans Affairs (VA). Our model accounted for patient censoring. Harrell’s c-index for our model using only features available at the time of diagnosis was 0.757 95% confidence interval [0.756, 0.757]. Our results show that machine learning methods like XGBoost can be adapted to use accelerated failure time (AFT) with censoring to model long-term risk of disease progression. Furthermore, the long median survival justifies and requires censoring. Overall, we show that an existing machine learning approach can be used for AFT outcome modeling in prostate cancer, and more generally for other chronic diseases with long observation times.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Mechanistic modelling of SARS-CoV-2 and other infectious diseases and the effects of therapeutics

Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical and modeling communities during the early days of the AIDS epidemic. Its successes lead to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus (HBV) and cytomegalovirus (CMV), which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus (RSV), West Nile virus (WNV), Zika virus, and SAR-CoV-2, which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. Furthermore, we then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize non-pharmaceutical and pharmaceutical interventions of the COVID-19 pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein “Everything should be made as simple as possible, but not simpler”, and this idea underlies the modeling we describe below.

60 APPLIED LIFE SCIENCES↗

Hearing impairment and tinnitus among older construction workers employed at DOE facilities

Few studies have defined the risk of hearing impairment and tinnitus after retirement. This report measures hearing impairment and tinnitus prevalence among older construction trades workers. The study cohort included 21,340 participants in a national medical screening program. Audiometric hearing impairment was classified according to the Global Burden of Disease Study. Tinnitus was determined by self-report. An internal subcohort of nonconstruction trades workers served as a reference group. Stratified analyses and multivariate analyses were used to measure the prevalence of hearing impairment and tinnitus by age, sex, and job category. Prevalence of any hearing impairment was 55.2% (males, 57.7%; females, 26.8%) and increased rapidly with age. Construction trades workers were 40% more likely to have hearing impairment than the reference group. The overall prevalence of tinnitus was 46.52% and followed patterns similar to hearing impairment. Workers with hearing impairment were more likely to also have tinnitus, but tinnitus was frequently reported in the absence of measured hearing impairment. Hearing impairment and tinnitus prevalence were much higher in this study than in previous research. A significant reason for the difference is that BTMed follows participants after they have retired. To draw conclusions about the risk for work-related chronic diseases and disorders it is important to monitor workers through their lifetimes. Also, tinnitus by itself should be given greater significance. We report the findings reinforce the need to promote noise reduction and hearing conservation in construction.

60 APPLIED LIFE SCIENCES↗

Optimizing Individualized Treatment Planning for Parkinson’s Disease Using Deep Reinforcement Learning

More than one million people currently live with Parkinson's Disease (PD) in the U.S. alone. Medications, such as levodopa, can help manage PD symptoms. However, medication treatment planning is generally based on patient history and limited interaction between physicians and patients during office visits. This limits the extent of benefit that may be derived from the treatment as disease/patient characteristics are generally non-stationary. Wearable sensors that provide continuous monitoring of various symptoms, such as bradykinesia and dyskinesia, can enhance symptom management. However, using such data to overhaul the current static medication treatment planning approach and prescribe personalized medication timing and dosage that accounts for patient/care-giver/physician feedback/preferences remains an open question. We develop a model to prescribe timing and dosage of medications, given the motor fluctuation data collected using wearable sensors in real-time. We solve the resulting model using deep reinforcement learning (DRL). The prescribed policy determines the optimal treatment plan that minimizes patient's symptoms. Our results show that the model-prescribed policy outperforms the static a priori treatment plan in improving patients' symptoms, providing a proof-of-concept that DRL can augment medical decision making for treatment planning of chronic disease patients.

Watts, Jeremy↗

Microcystin-LR aerosol induces inflammatory responses in healthy human primary airway epithelium

Harmful algal blooms plague bodies of freshwater globally. These blooms are often composed of outgrowths of cyanobacteria capable of producing the heptapeptide Microcystin-LR (MC-LR) which is a well-known hepatotoxin. Recently, MC-LR has been detected in aerosols generated from lake water. However, the risk for human health effects due to MC-LR inhalation exposure have not been extensively investigated. In this study, we exposed a fully differentiated 3D human airway epithelium derived from 14 healthy donors to MC-LR-containing aerosol for 3 minutes per day for 3 days. Concentrations of MC-LR ranged from 100 pM to 1 µM. Although there were little to no detrimental alterations in measures of the airway epithelial function (i.e. cell survival, tissue integrity, mucociliary clearance, or cilia beating frequency), a distinct shift in the transcriptional activity was found. Genes related to inflammation were found to be upregulated such as C-C motif chemokine 5 (CCL5; log2FC = 0.56 , p = 0.02) and C-C chemokine receptor type 7 (CCR7; log2FC = 0.83, p = 0.03). Functionally, conditioned media from MC-LR exposed airway epithelium was also found to have significant chemo-attractive properties for primary human neutrophils. Additionally, increases were found in the concentration of secreted chemokine proteins in the conditioned media such as CCL1 (log2FC = 5.07 , p = 0.0001) and CCL5 (log2FC = 1.02, p = 0.046). These results suggest that MC-LR exposure to the human airway epithelium is capable of inducing an inflammatory response that may potentiate acute or chronic disease.

3D human airway epithelium↗

Vascular endothelial and smooth muscle cell galvanotactic response and differential migratory behavior

Chronic disease or injury of the vasculature impairs the functionality of vascular wall cells particularly in their ability to migrate and repair vascular surfaces. Under pathologic conditions, vascular endothelial cells (ECs) lose their non-thrombogenic properties and decrease their motility. Alternatively, vascular smooth muscle cells (SMCs) may increase motility and proliferation, leading to blood vessel luminal invasion. Current therapies to prevent subsequent blood vessel occlusion commonly mechanically injure vascular cells leading to endothelial denudation and smooth muscle cell luminal migration. Due to this dichotomous migratory behavior, a need exists for modulating vascular cell growth and migration in a more targeted manner. Here, we examine the efficacy of utilizing small direct current electric fields to influence vascular cell-specific migration (“galvanotaxis”). We designed, fabricated, and implemented an in vitro chamber for tracking vascular cell migration direction, distance, and displacement under galvanotactic influence of varying magnitude. Our results indicate that vascular ECs and SMCs have differing responses to galvanotaxis; ECs exhibit a positive correlation of anodal migration while SMCs exhibit minimal change in directional migration in relation to the electric field direction. SMCs exhibit less motility response (i.e. distance traveled in 4 h) compared to ECs, but SMCs show a significantly higher motility at low electric potentials (80 mV/cm). With further investigation and translation, galvanotaxis may be an effective solution for modulation of vascular cell-specific migration, leading to enhanced endothelialization, with coordinate reduced smooth muscle in-migration.

60 APPLIED LIFE SCIENCES↗

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18–72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18–73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I 2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen’s d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

59 BASIC BIOLOGICAL SCIENCES↗

Convergent use of phosphatidic acid for hepatitis C virus and SARS-CoV-2 replication organelle formation

Double membrane vesicles (DMVs) serve as replication organelles of plus-strand RNA viruses such as hepatitis C virus (HCV) and SARS-CoV-2. Viral DMVs are morphologically analogous to DMVs formed during autophagy, but lipids driving their biogenesis are largely unknown. Here we show that production of the lipid phosphatidic acid (PA) by acylglycerolphosphate acyltransferase (AGPAT) 1 and 2 in the ER is important for DMV biogenesis in viral replication and autophagy. Using DMVs in HCV-replicating cells as model, we found that AGPATs are recruited to and critically contribute to HCV and SARS-CoV-2 replication and proper DMV formation. An intracellular PA sensor accumulated at viral DMV formation sites, consistent with elevated levels of PA in fractions of purified DMVs analyzed by lipidomics. Apart from AGPATs, PA is generated by alternative pathways and their pharmacological inhibition also impaired HCV and SARS-CoV-2 replication as well as formation of autophagosome-like DMVs. These data identify PA as host cell lipid involved in proper replication organelle formation by HCV and SARS-CoV-2, two phylogenetically disparate viruses causing very different diseases, i.e. chronic liver disease and COVID-19, respectively. Host-targeting therapy aiming at PA synthesis pathways might be suitable to attenuate replication of these viruses.

60 APPLIED LIFE SCIENCES↗

Niacin for Parkinson's disease

Abstract Parkinson's disease (PD) is a neurodegenerative disease associated with progressive loss of motor function and cognitive decline occurring in 1% of the USA population. There is no cure for PD, and current treatment regimens are directed towards treating symptoms and not treating the underlying cause of the disease. Chronic neuroinflammation is associated with loss of neuronal cells, leading to motor and cognitive decline. Current clinical trials on drugs and nutraceuticals, such as coenzyme Q10 and niacin, are being carried out to delay progression and reduce damage by inflammatory molecules, such as reactive oxygen species and cytokines, in PD patients. In this review, we present available clinical trials and the role of niacin in reducing neuroinflammation in PD.

Seamon, Marissa↗

Reducing nighttime light exposure in the urban environment to benefit human health and society

Nocturnal light pollution can have profound effects on humans and other organisms. Recent research indicates that nighttime outdoor lighting is increasing rapidly. Evidence from controlled laboratory studies demonstrates that nocturnal light exposure can strain the visual system, disrupt circadian physiology, suppress melatonin secretion, and impair sleep. There is a growing body of work pointing to adverse effects of outdoor lighting on human health, including the risk of chronic diseases, but this knowledge is in a more nascent stage. In this Review, we synthesize recent research on the context-specific factors and physiology relevant to nocturnal light exposure in relation to human health and society, identify critical areas for future research, and highlight recent policy steps and recommendations for mitigating light pollution in the urban environment.

Science & Technology - Other Topics↗

Examining Perceptions of Spanish Language Health Information Among Hispanics Living in the United States: A Qualitative Study Assessing Videos, Brochures, and Websites

Background Nationally, Hispanics experience health disparities manifested as a higher prevalence of chronic diseases in comparison to non-Hispanic Whites. Factors that influence health disparities in this population include inadequate dissemination of culturally and linguistically appropriate health information. Method Our qualitative analysis is based on data obtained from three focus groups with Spanish-speaking Hispanic adults conducted at a clinic in Nebraska. Participants were asked about their perceptions of health information in the form of videos, brochures, and websites. We followed the consolidated criteria for reporting qualitative research and used the theoretical framework of content analysis. Results For videos, attributes associated with higher levels of trust included a friendly health professional, the logo or name of a health care institute, and a reference specifying “se habla Español.” For brochures, attributes associated with trust included use of visual aids, use of numerous colors and big font sizes, the year of printing, and a health care agency logo. For websites, characteristics associated with trust were inclusion of plain language, use of pictures and videos, and date of last update. In all focus groups, participants perceived the use of mixed English/Spanish language in health information from pamphlets and websites as unprofessional. The use of unknown governmental logos in health promotional videos and websites was perceived as untrustworthy information. Conclusions Spanish-speaking Hispanics prefer health information supported by a health care agency or delivered by a health care professional. Health communication strategies should avoid the use of mixed English/Spanish language in sensitive information especially when combined with governmental logos.

De Alba Rosales, Armando↗

Xanthohumol microbiome and signature in healthy adults (the XMaS trial): a phase I triple-masked, placebo-controlled clinical trial

Natural products may provide a source for the discovery and development of adjunctive pharmacological interventions to modulate the inflammatory pathways contributing to chronic disease. Xanthohumol, a flavonoid from the hops plant (Humulus lupulus), has antioxidant and anti-inflammatory properties and may act as a prebiotic to the intestinal microbiota. Xanthohumol is not currently approved as a drug by the US Food and Drug Administration (FDA), but is available as a dietary supplement and ingredient in medical foods. To formally test the safety of xanthohumol, a phase I clinical trial (“XMaS”) was designed and approved under an Investigational New Drug application to the US FDA. The main objective is to examine the clinical safety and subjective tolerability of xanthohumol in healthy adults compared to placebo. Additional aims are to monitor biomarkers related to inflammation, gut permeability, bile acid metabolism, routes, and in vivo products of xanthohumol metabolism, and to evaluate xanthohumol’s impact on gut microbial composition.

60 APPLIED LIFE SCIENCES↗

bmdrc: Python package for quantifying phenotypes from chemical exposures with benchmark dose modeling

Though chemical exposures are known to potentially have negative impacts on health, including contributing to chronic diseases such as cancer, the quantitative contribution of risk is not fully understood for every chemical. A commonly used approach to quantify levels of risk is to measure the proportion of organisms (such as a total number of zebrafish on a plate or mice in a cage) with abnormal behavioral responses or morphology at increasing concentrations of chemical exposure. A particular challenge with processing the proportional data from these assays is the appropriate estimation of chemical concentration levels that result in malformations or acute toxicity, as these values typically vary between experimental measurements. The recommended approach by the Environmental Protection Agency (EPA) is to fit benchmark dose curves with specific filters and model fitting steps, which are crucial to properly processing the proportional data. Several tools exist for the fitting of benchmark dose response curves, but none are standalone Python libraries built to process both morphological and behavioral data as proportions with all the EPA recommended filters, filter parameters, models, and model parameters. Thus, here we present the benchmark dose response curve (bmdrc) Python library, which was built to closely follow these EPA guidelines with helpful visualizations of filters and fitted model curves, and reports for reproducibility purposes. bmdrc is open-source and has demonstrated utility as a support package to an existing web portal for information on chemicals (https://srp.pnnl.gov). Our package will support any toxicology analysis where the response is a proportional value at increasing levels of a concentration of a chemical or chemical mixture.

Superfund↗

Misclassification of primary liver cancer in the Life Span Study of atomic bomb survivors

Primary liver cancer is difficult to diagnose accurately at death, due to metastases from nearby organs and to concomitant diseases, such as chronic hepatitis and cirrhosis. Trends in diagnostic accuracy could affect radiation risk estimates for incident liver cancer by altering background rates or by impacting risk modification by sex and age. We quantified the potential impact of death‐certificate inaccuracies on radiation risk estimates for liver cancer in the Life Span Study of atomic bomb survivors. True‐positive and false‐negative rates were obtained from a previous study that compared death‐certificate causes of death with those based on pathological review, from 1958 to 1987. We assumed various scenarios for misclassification rates after 1987. We obtained estimated true positives and estimated false negatives by stratified sampling from binomial distributions with probabilities given by the true‐positive and false‐negative rates, respectively. Poisson regression methods were applied to highly stratified person‐year tables of corrected case counts and accrued person years. During the study period (1958–2009), there were 1,885 cases of liver cancer, which included 383 death‐certificate‐only (DCO) cases; 1,283 cases with chronic liver disease as the underlying cause of death; and 150 DCO cases of pancreatic cancer among 105,444 study participants. Across the range of scenarios considered, radiation risk estimates based on corrected case counts were attenuated, on average, by 13–30%. Our results indicated that radiation risk estimates for liver cancer were potentially sensitive to death‐certificate inaccuracies. Additional data are needed to inform misclassification rates in recent years.

French, Benjamin↗