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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

An approach to and web-based tool for infectious disease outbreak intervention analysis

Infectious diseases are a leading cause of death globally. Decisions surrounding how to control an infectious disease outbreak currently rely on a subjective process involving surveillance and expert opinion. However, there are many situations where neither may be available. Modeling can fill gaps in the decision making process by using available data to provide quantitative estimates of outbreak trajectories. Effective reduction of the spread of infectious diseases can be achieved through collaboration between the modeling community and public health policy community. However, such collaboration is rare, resulting in a lack of models that meet the needs of the public health community. Here we show a Susceptible-Infectious-Recovered (SIR) model modified to include control measures that allows parameter ranges, rather than parameter point estimates, and includes a web user interface for broad adoption. We apply the model to three diseases, measles, norovirus and influenza, to show the feasibility of its use and describe a research agenda to further promote interactions between decision makers and the modeling community.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Multimodal LA-ICP-MS and nanoSIMS imaging enables copper mapping within photoreceptor megamitochondria in a zebrafish model of Menkes disease

Here, copper is essential for eukaryotic life, and animals must acquire this nutrient through the diet and distribute it to cells and organelles for proper function of biological targets. Indeed, mutations in the central copper exporter ATP7A contribute to a spectrum of diseases, including Menkes disease, with symptoms ranging from neurodegeneration to lax connective tissue. As such, a better understanding of the fundamental impacts of ATP7A mutations on in vivo copper distributions is of relevance to those affected by these diseases. For this work, we combine metal imaging and optical imaging techniques at a variety of spatial resolutions to identify tissues and structures with altered copper levels in the Calamity gw71 zebrafish model of Menkes disease. Rapid profiling of tissue slices with LA-ICP-MS identified reduced copper levels in the brain, neuroretina, and liver of Menkes fish compared to control specimens. High resolution nanoSIMS imaging of the neuroretina, combined with electron and confocal microscopies, identified the megamitochondria of photoreceptors as loci of copper accumulation in wildtype fish, with lower levels of megamitochondrial copper observed in Calamity gw71 zebrafish. Interestingly, this localized copper decrease does not result in impaired photoreceptor development or altered megamitochondrial morphology, suggesting the prioritization of copper at sufficient levels for maintaining essential mitochondrial functions. Together, these data establish the Calamity gw71 zebrafish as an optically transparent in vivo model for the study of neural copper misregulation, illuminate a role for the ATP7A copper exporter in trafficking copper to the neuroretina, and highlight the utility of combining multiple imaging techniques for studying metals in whole organism settings with spatial resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Effect of Genetic Diagnosis on Patients with Previously Undiagnosed Disease

Background. Despite extensive medical evaluation many patients with chronic disease remain without a diagnosis. The Undiagnosed Diseases Network (UDN) was established to embrace the most challenging cases in medicine and to characterize the biology of newly discovered diseases. Methods. The UDN was formed in 2014 as a National Institutes of Health (NIH)-funded network of seven clinical sites, two sequencing cores, and a coordinating center. Later a central biorepository, metabolomics core, and model organisms screening center were added. We undertook a retrospective evaluation of the patients referred since the network formed to evaluate the efficacy of this approach. Results. Between September 16, 2015 and May 23, 2017, 1519 patients were referred to the network (53% female). Six hundred and one cases (40%) were accepted for evaluation (53% female). Of those accepted, 192 (32%) had previously undergone exome sequencing. The most common primary symptom categories of accepted patients were neurological (40%), musculoskeletal (9.7%), immunological (6.8%), gastrointestinal (6.5%), and rheumatological (5.7%). The number of completed evaluations on May 23, 2017, was 365, at which time, 100 patients had received diagnoses. In the intervening period, a further 25 received a diagnosis indicating a network diagnosis rate of 34%. Some diagnoses were made from clinical review alone (10%). Many were informed through sequencing the exomes or genomes of the patient or family (72%). A majority of diagnoses (83%) were deemed medically actionable by the clinical team. Indeed, of the total, 30% led to changes in therapy, 24% led to changes in the diagnostic workup, and 28% allowed variant-specific genetic counseling. Through the combined work of the network, a total of 24 new syndromes were defined. Conclusions. A collaborative network with access to state-of-the-art diagnostic tools can expand the medical record of human disease providing actionable clinical diagnoses to a substantial majority of those patients.

Splinter, Kimberly↗
DOE OSTI2018

Mechanics of diseased red blood cells in human spleen and consequences for hereditary blood disorders

In red blood cell (RBC) diseases, the spleen contributes to anemia by clearing the damaged RBCs, but its unique ability to mechanically challenge RBCs also poses the risk of inducing other pathogenic effects. We have analyzed RBCs in hereditary spherocytosis (HS) and hereditary elliptocytosis (HE), two typical examples of blood disorders that result in membrane protein defects in RBCs. We use a two-component protein-scale RBC model to simulate the traversal of the interendothelial slit (IES) in the human spleen, a stringent biomechanical challenge on healthy and diseased RBCs that cannot be directly observed in vivo. In HS, our results confirm that the RBC loses surface due to weakened cohesion between the lipid bilayer and the cytoskeleton and reveal that surface loss may result from vesiculation of the RBC as it crosses IES. In HE, traversing IES induces sustained elongation of the RBC with impaired elasticity and fragmentation in severe disease. Our simulations thus suggest that in inherited RBC disorders, the spleen not only filters out pathological RBCs but also directly contributes to RBC alterations. These results provide a mechanistic rationale for different clinical outcomes documented following splenectomy in HS patients with spectrin-deficient and ankyrin-deficient RBCs and offer insights into the pathogenic role of human spleen in RBC diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Comparative genome analyses suggest a hemibiotrophic lifestyle and virulence differences for the beech bark disease fungal pathogens Neonectria faginata and Neonectria coccinea

Abstract Neonectria faginata and Neonectria coccinea are the causal agents of the insect-fungus disease complex known as beech bark disease (BBD), known to cause mortality in beech forest stands in North America and Europe. These fungal species have been the focus of extensive ecological and disease management studies, yet less progress has been made toward generating genomic resources for both micro- and macro-evolutionary studies. Here, we report a 42.1 and 42.7 mb highly contiguous genome assemblies of N. faginata and N. coccinea, respectively, obtained using Illumina technology. These species share similar gene number counts (12,941 and 12,991) and percentages of predicted genes with assigned functional categories (64 and 65%). Approximately 32% of the predicted proteomes of both species are homologous to proteins involved in pathogenicity, yet N. coccinea shows a higher number of predicted mitogen-activated protein kinase genes, virulence determinants possibly contributing to differences in disease severity between N. faginata and N. coccinea. A wide range of genes encoding for carbohydrate-active enzymes capable of degradation of complex plant polysaccharides and a small number of predicted secretory effector proteins, secondary metabolite biosynthesis clusters and cytochrome oxidase P450 genes were also found. This arsenal of enzymes and effectors correlates with, and reflects, the hemibiotrophic lifestyle of these two fungal pathogens. Phylogenomic analysis and timetree estimations indicated that the N. faginata and N. coccinea species divergence may have occurred at ∼4.1 million years ago. Differences were also observed in the annotated mitochondrial genomes as they were found to be 81.7 kb (N. faginata) and 43.2 kb (N. coccinea) in size. The mitochondrial DNA expansion observed in N. faginata is attributed to the invasion of introns into diverse intra- and intergenic locations. These first draft genomes of N. faginata and N. coccinea serve as valuable tools to increase our understanding of basic genetics, evolutionary mechanisms and molecular physiology of these two nectriaceous plant pathogenic species.

Salgado-Salazar, Catalina↗
DOE OSTI2022

Fire, insect and disease‐caused tree mortalities increased in forests of greater structural diversity during drought

Abstract Structural diversity is an emerging dimension of biodiversity that accounts for size variations in organs among individuals in a community. Previous studies show significant effects of structural diversity on forest growth, but its effects on forest mortality are not known, particularly at a large scale. To address this knowledge gap, we quantified structural diversity using stem structural diversity (SSD) based on both tree diameter and height. We obtained U.S. Forest Service Forest Inventory and Analysis (FIA) data from over 2400 plots across southcentral U.S. forests that have suffered a recent drought. Using data from multiple sampling times, we calculated SSD and compared the relative importance of SSD, species diversity, functional diversity and other stand attributes in determining tree mortalities caused by fire, insects and diseases. We also used FIRETEC, a physics‐based fire model, to test the effect of SSD on canopy consumption by fire. Our results showed that (1) SSD was positively associated with tree mortalities caused by all three disturbances; (2) species richness was negatively associated with insect‐ and disease‐caused mortalities; (3) functional diversity was negatively associated with fire‐ and disease‐caused mortalities and (4) more phylogenetically related species had more similar mortality rates by insect and disease but not fire. Moreover, the FIRETEC model showed increasing canopy consumption by fire in stands with greater SSD. Together, the different tree mortalities during drought associated with SSD more consistently than the other biodiversity metrics were evaluated. Synthesis . Our results suggest that SSD could be considered in modelling forest dynamics and planning management to sustain forest health under disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

T cell activation is insufficient to drive SIV disease progression

Resolution of T cell activation and inflammation is a key determinant of the lack of SIV disease progression in African green monkeys (AGMs). Although frequently considered together, T cell activation occurs in response to viral stimulation of acquired immunity, while inflammation reflects innate immune responses to mucosal injury. We dissociated T cell activation from inflammation through regulatory T cell (Treg) depletion with Ontak (interleukin-2 coupled with diphtheria toxin) during early SIV infection of AGMs. This intervention abolished control of T cell immune activation beyond the transition from acute to chronic infection. Ontak had no effect on gut barrier integrity, microbial translocation, inflammation, and hypercoagulation, despite increasing T cell activation. Ontak administration increased macrophage counts yet decreased their activation. Persistent T cell activation influenced SIV pathogenesis, shifting the ramp-up in viral replication to earlier time points, prolonging the high levels of replication, and delaying CD4 + T cell restoration yet without any clinical or biological sign of disease progression in Treg-depleted AGMs. Thus, by inducing T cell activation without damaging mucosal barrier integrity, we showed that systemic T cell activation per se is not sufficient to drive disease progression, which suggests that control of systemic inflammation (likely through maintenance of gut integrity) is the key determinant of lack of disease progression in natural hosts of SIVs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Synthetic method of analogues for emerging infectious disease forecasting

The Method of Analogues (MOA) has gained popularity in the past decade for infectious disease forecasting due to its non-parametric nature. In MOA, the local behavior observed in a time series is matched to the local behaviors of several historical time series. The known values that directly follow the historical time series that best match the observed time series are used to calculate a forecast. This non-parametric approach leverages historical trends to produce forecasts without extensive parameterization, making it highly adaptable. However, MOA is limited in scenarios where historical data is sparse. This limitation was particularly evident during the early stages of the COVID-19 pandemic, where the emerging global epidemic had little-to-no historical data. In this work, we propose a new method inspired by MOA, called the Synthetic Method of Analogues (sMOA). sMOA replaces historical disease data with a library of synthetic data that describe a broad range of possible disease trends. This model circumvents the need to estimate explicit parameter values by instead matching segments of ongoing time series data to a comprehensive library of synthetically generated segments of time series data. We demonstrate that sMOA has competitive performance with state-of-the-art infectious disease forecasting models, out-performing 78% of models from the COVID-19 Forecasting Hub in terms of averaged Mean Absolute Error and 76% of models from the COVID-19 Forecasting Hub in terms of averaged Weighted Interval Score. Additionally, we introduce a novel uncertainty quantification methodology designed for the onset of emerging epidemics. Developing versatile approaches that do not rely on historical data and can maintain high accuracy in the face of novel pandemics is critical for enhancing public health decision-making and strengthening preparedness for future outbreaks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Semi-Analytical Hierarchical Bayesian Inference of Nonlinear Model Structure in Stochastic Dynamics: Applied to Compartmental Models of Infectious Diseases

A Bayesian computational framework for parsimonious inference in stochastic nonlinear dynamical systems is presented. This framework enables the concurrent estimation of system states, time-varying parameters, time-invariant parameters, and the optimal sparsity structure of the model parameters. Because differential equation-based models are often simplified mechanistic or phenomenological representations, robust inference from noisy measurement data requires explicit treatment of model error and uncertainty. Model error and time-varying parameters can be represented as random processes, enabling inference while making minimal assumptions about the underlying sources of discrepancy and variability. Adopting stochastic differential equation representations affords the model significant flexibility, but can also render it susceptible to overfitting during statistical inversion, where the inferred model may track noise rather than the underlying signal. To alleviate the effects of overfitting and to enable the discovery of the optimal sparse representation of the time-invariant parameters, a Bayesian sparse learning algorithm is embedded within the framework. This sparse learning framework adopts an approximate hierarchical Bayesian setting defined by a series of semi-analytical expressions. The model structure inference framework is validated using a stochastic compartmental model for tracking and forecasting active cases of an infectious disease. Compartmental models describe population-level infectious disease dynamics through interactions among population fractions grouped by disease state. Mathematically, such models consist of a system of coupled ordinary differential equations. This example adopts an expressive compartmental model that includes multiple possible interactions between disease states, motivated by early uncertainty surrounding COVID-19 reinfection dynamics and their implications for long-term epidemic forecasting. The sparse learning exercise permits the inference of a priori unknown epidemiological dynamics from simulated public health data, discovering the nested compartmental model that optimizes the trade-off between average data-fit and model complexity. It is shown that inducing sparsity among the model parameters eliminates redundant interactions between compartments, equivalently revealing the optimal coupling structure between differential equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

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↗
DOE OSTI2020

The Differential Equations That Model Diseases

In this brief tutorial, I will describe the simplest way of modeling a deadly infectious disease, such as COVID-19. I will show that at early times, the disease grows exponentially, but at late times, falls off like a Bell curve. I will solve the equations numerically with Python. A common mathematical model is the so-called compartmental model, where diseases can move people between "categories" such as healthy, infectious, or truly sick. This is a large, well established field and there are many good resources on this topic. I started with the SIAM review article The mathematics of infectious diseases. However, there are many excellent textbooks and more modern reviews as well.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Double-Pronged Sword: XJB-5-131 Is a Suppressor of Somatic Instability and Toxicity in Huntington’s Disease

Due to large increases in the elderly populations across the world, age-related diseases are expected to expand dramatically in the coming years. Among these, neurodegenerative diseases will be among the most devastating in terms of their emotional and economic impact on patients, their families, and associated subsidized health costs. There is no currently available cure or rescue for dying brain cells. Viable therapeutics for any of these disorders would be a breakthrough and provide relief for the large number of affected patients and their families. Neurodegeneration is accompanied by elevated oxidative damage and inflammation. While natural antioxidants have largely failed in clinical trials, preclinical phenotyping of the unnatural, mitochondrial targeted nitroxide, XJB-5-131, bodes well for further translational development in advanced animal models or in humans. Here we consider the usefulness of synthetic antioxidants for the treatment of Huntington’s disease. The mitochondrial targeting properties of XJB-5-131 have great promise. It is both an electron scavenger and an antioxidant, reducing both somatic expansion and toxicity simultaneously through the same redox mechanism. By quenching reactive oxygen species, XJB-5-131 breaks the cycle between the rise in oxidative damage during disease progression and the somatic growth of the CAG repeat which depends on oxidation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Identification of Colletotrichum aenigma as the new causal agent of leaf blight disease on Aucuba japonica Thunb., and screenings of effective fungicides for its sustainable management

Aucuba japonica Thunb is an evergreen woody ornamental plant with significant economic and ecological values. It also produces aucubin, showing a variety of biological activities. It is widely planted in the southwest region of China, including karst landscape areas in Guizhou Province. In January 2022, a serious leaf blight disease was observed on the leaves of A. japonica in the outdoor gardens of Guizhou University, Guiyang, Guizhou, China. The causal agent was identified as Colletotrichum aenigma through amplification and sequencing of the internal transcribed spacer (ITS) region, translation of the chitin synthase ( CHS ) and actin ( ACT ) genes, and morphological characterizations. Koch’s postulates were confirmed by its pathogenicity on healthy leaves, including re-isolation and identification. To our knowledge, this is the first report of C. aenigma causing leaf blight on A. japonica worldwide. To identify pathogen characteristics that could be utilized for future disease management, the effects of temperature and light on mycelial growth, conidia production, and conidial germination, and the effects of humidity on conidial germination were studied. Optimal temperatures for mycelial growth of C. aenigma BY827 were 25–30°C, while 15°C and 35°C were favorable for conidia production. Concurrently, alternating 10-h light and 14-h dark, proved to be beneficial for mycelial growth and conidial germination. Additionally, conidial germination was enhanced at 90% humidity. In vitro screenings of ten chemical pesticides to assess their efficacy in suppressing C. aenigma representative strain BY827. Among them, difenoconazole showed the best inhibition rate, with an EC 50 (concentration for 50% of maximal effect) value of 0.0148 μg/ml. Subsequently, field experiment results showed that difenoconazole had the highest control efficiency on A. japonica leaf blight (the decreasing rate of disease incidence and decreasing rate of disease index were 44.60 and 47.75%, respectively). Interestingly, we discovered that C. aenigma BY827 may develop resistance to mancozeb, which is not reported yet among Colletotrichum spp. strains. In conclusion, our study provided new insights into the causal agent of A. japonica leaf blight, and the effective fungicides evaluated provided an important basis and potential resource for the sustainable control of A. japonica leaf blight caused by C. aenigma in the field.

Fan, Ruidong↗
DOE OSTI2020

From Prevention to Disease Perturbations: A Multi-Omic Assessment of Exercise and Myocardial Infarctions

While a molecular assessment of the perturbations and injury arising from diseases is essential in their diagnosis and treatment, understanding changes due to preventative strategies is also imperative. Currently, complex diseases such as cardiovascular disease (CVD), the leading cause of death worldwide, suffer from a limited understanding of how the molecular mechanisms taking place following preventive measures (e.g., exercise) differ from changes occurring due to the injuries caused from the disease (e.g., myocardial infarction (MI)). Therefore, this manuscript assesses lipidomic changes before and one hour after exercise treadmill testing (ETT) and before and one hour after a planned myocardial infarction (PMI) in two separate patient cohorts. Strikingly, unique lipidomic perturbations were observed for these events, as could be expected from their vastly different stresses on the body. The lipidomic results were then combined with previously published metabolomic characterizations of the same patients. This integration provides complementary insights into the exercise and PMI events, thereby giving a more holistic understanding of the molecular changes associated with each.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Evolution of Medical Countermeasures for Ebola Virus Disease: Lessons Learned and Next Steps

The Ebola virus disease outbreak that occurred in Western Africa from 2013–2016, and subsequent smaller but increasingly frequent outbreaks of Ebola virus disease in recent years, spurred an unprecedented effort to develop and deploy effective vaccines, therapeutics, and diagnostics. This effort led to the U.S. regulatory approval of a diagnostic test, two vaccines, and two therapeutics for Ebola virus disease indications. Moreover, the establishment of fieldable diagnostic tests improved the speed with which patients can be diagnosed and public health resources mobilized. The United States government has played and continues to play a key role in funding and coordinating these medical countermeasure efforts. Here, we describe the coordinated U.S. government response to develop medical countermeasures for Ebola virus disease and we identify lessons learned that may improve future efforts to develop and deploy effective countermeasures against other filoviruses, such as Sudan virus and Marburg virus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

MicroRNAs as diagnostic and therapeutic tools for Alzheimer’s disease: advances and limitations

Alzheimer’s disease (AD) is the most common age-related, progressive neurodegenerative disease. It is characterized by memory loss and cognitive decline and responsible for most cases of dementia in the elderly. Late-onset or sporadic AD accounts for > 95% of cases, with age at onset > 65 years. Currently there are no drugs or other therapeutic agents available to prevent or delay the progression of AD. The cellular and molecular changes occurring in the brains of individuals with AD include accumulation of β-amyloid peptide and hyperphosphorylated tau protein, decrease of acetylcholine neurotransmitter, inflammation, and oxidative stress. Aggregation of β-amyloid peptide in extracellular plaques and the hyperphosphorylated tau protein in intracellular neurofibrillary tangles are characteristic of AD. A major challenge is identifying molecular biomarkers of the early-stage AD in patients as most studies have been performed with blood or brain tissue samples (postmortem) at late-stage AD. Subjects with mild cognitive impairment almost always have the neuropathologic features of AD with about 50% of mild cognitive impairment patients progressing to AD. They could provide important information about AD pathomechanism and potentially also highlight minimally or noninvasive, easy-to-access biomarkers. MicroRNAs are dysregulated in AD, and may facilitate the early detection of the disease and potentially the continual monitoring of disease progression and allow therapeutic interventions to be evaluated. Four recent reviews have been published of microRNAs in AD, each of which identified areas of weakness or limitations in the reported studies. Importantly, studies in the last three years have shown considerable progress in overcoming some of these limitations and identifying specific microRNAs as biomarkers for AD and mild cognitive impairment. Further large-scale human studies are warranted with less disparity in the study populations, and using an appropriate method to validate the findings.

Cell Biology↗
NASA NTRS1991

Technologies for the marketplace from the Centers for Disease Control

The Centers for Disease Control, a Public Health Service agency, is responsible for the prevention and control of disease and injury. Programs range from surveillance and prevention of chronic and infectious diseases to occupational health and injury control. These programs have produced technologies in a variety of fields, including vaccine development, new methods of disease diagnosis, and new tools to ensure a safer work environment.

Reid-Sanden, Frances L.↗
NASA NTRS1996

Use of Remote Sensing Surveillance to Monitor Environmental Parameters Associated with Mosquito Abundance and Vector-borne Diseases

Lymphatic filariasis persists as a major cause of clinical morbidity and a significant impediment to socioeconomic development in various parts of the world including Egypt. In Egypt, filariasis has been endemic since time immemorial. Early epidemiologic studies identified Culex pipiens L. as the main vector of the disease and also showed that the geographic distribution of the disease is highly focal and concentrated in lower Egypt. Between 1950 and 1965, a large scale filariasis control program was carried out by the Egyptian Ministry of Health (EMOH) in the endemic areas. Control efforts led to a steady decrease of the disease in areas of the country previously identified as endemic. However, spot surveys conducted in various parts of the Nile Delta during the 1970's and 1980's revealed that the downward trend of the disease had stopped and that the prevalence and intensity of microfilaraemia had increased.

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