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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Role of tau versus TDP-43 pathology on medial temporal lobe atrophy in aging and Alzheimer's disease

Hippocampal atrophy on magnetic resonance imaging is an important biomarker in Alzheimer's disease (AD). While hippocampal atrophy was thought to result from tau tangles in AD, different neuropathologies can lead to hippocampal atrophy, especially TAR DNA-binding protein 43 (TDP-43) pathology. In this narrative review, we evaluate existing studies on the relative contribution of tau and TDP-43 pathology to medial temporal lobe (MTL) atrophy. We report a clear association of both tau and TDP-43 neuropathology with MTL atrophy, even after correcting for other neuropathologies. Next, we discuss a potential synergism between tau and TDP-43 and the relative timing of the effects of both neuropathologies. Finally, avenues for future research will be discussed. A better understanding of the interplay between tau and TDP-43 neuropathologies and their effect on atrophy will help with the development of more specific biomarkers for limbic-predominant age-related TDP-43 encephalopathy and pinpointing of the optimal timing for testing anti-tau and anti-TDP-43 treatments in trials.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Development of message passing-based graph convolutional networks for classifying cancer pathology reports

Abstract Background Applying graph convolutional networks (GCN) to the classification of free-form natural language texts leveraged by graph-of-words features (TextGCN) was studied and confirmed to be an effective means of describing complex natural language texts. However, the text classification models based on the TextGCN possess weaknesses in terms of memory consumption and model dissemination and distribution. In this paper, we present a fast message passing network (FastMPN), implementing a GCN with message passing architecture that provides versatility and flexibility by allowing trainable node embedding and edge weights, helping the GCN model find the better solution. We applied the FastMPN model to the task of clinical information extraction from cancer pathology reports, extracting the following six properties: main site, subsite, laterality, histology, behavior, and grade. Results We evaluated the clinical task performance of the FastMPN models in terms of micro- and macro-averaged F1 scores. A comparison was performed with the multi-task convolutional neural network (MT-CNN) model. Results show that the FastMPN model is equivalent to or better than the MT-CNN. Conclusions Our implementation revealed that our FastMPN model, which is based on the PyTorch platform, can train a large corpus (667,290 training samples) with 202,373 unique words in less than 3 minutes per epoch using one NVIDIA V100 hardware accelerator. Our experiments demonstrated that using this implementation, the clinical task performance scores of information extraction related to tumors from cancer pathology reports were highly competitive.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Brain phosphoproteomic analysis identifies diabetes‐related substrates in Alzheimer's disease pathology in older adults

INTRODUCTION: Type 2 diabetes increases the risk of Alzheimer's disease (AD) dementia. Insulin signaling dysfunction exacerbates tau protein phosphorylation, a hallmark of AD pathology. However, the comprehensive impact of diabetes on patterns of AD-related phosphoprotein in the human brain remains underexplored. METHODS: We performed tandem mass tag–based phosphoproteome profiling in post mortem human brain prefrontal cortex samples from 191 deceased older adults with and without diabetes and pathologic AD. RESULTS: Among 7874 quantified phosphosites, microtubule-associated protein tau (MAPT) phosphorylated at T529 and T534 (isoform 8 T212 and T217) were more abundant in AD and showed differential associations with diabetes. Network analysis of co-abundance patterns uncovered synergistic interactions between AD and diabetes, with one module exhibiting higher MAPT phosphorylation (15 MAPT phosphosites) and another displaying lower MAP1B phosphorylation (22 MAP1B phosphosites). DISCUSSION: This study offers phosphoproteomics insights into AD in diabetes, shedding light on mechanisms that can inform the development of therapeutics for dementia. Highlights: The risk of Alzheimer's disease (AD) dementia is increased among older adults living with diabetes. The patterns of AD-related phosphoprotein in the human brain in older adults are differential among older adults living with diabetes. Microtubule-associated protein tau phosphorylated at T529 and T534 (isoform 8 T212 and T217) showed differential associations with diabetes. Phosphosite co-abundance networks of synergistic interactions between AD and diabetes were identified.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Using ensembles and distillation to optimize the deployment of deep learning models for the classification of electronic cancer pathology reports

One of the goals of the Surveillance, Epidemiology, and End Results (SEER) program is to estimate incidence, prevalence, and mortality of all cancers. To that end, cancer registries across the country maintain a massive database of cancer pathology reports which contain rich information to understand cancer trends. However, these reports are stored in the form of unstructured text, and human annotators are required to read and extract relevant information. In this article, we show that existing deep learning models for automating information extraction from cancer pathology reports can be significantly improved by using ensemble model distillation. We found that by training multiple predictive models and transferring their knowledge to a single, low-resource model, we can reduce the number of highly confident wrong predictions. Our results show that our implemented methods could save 1000s of manual annotation hours.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Evaluating algorithmic bias on biomarker classification of breast cancer pathology reports

Objectives: This work evaluated algorithmic bias in biomarkers classification using electronic pathology reports from female breast cancer cases. Bias was assessed across 5 subgroups: cancer registry, race, Hispanic ethnicity, age at diagnosis, and socioeconomic status. Materials and Methods: We utilized 594 875 electronic pathology reports from 178 121 tumors diagnosed in Kentucky, Louisiana, New Jersey, New Mexico, Seattle, and Utah to train 2 deep-learning algorithms to classify breast cancer patients using their biomarkers test results. We used balanced error rate (BER), demographic parity (DP), equalized odds (EOD), and equal opportunity (EOP) to assess bias. Results: We found differences in predictive accuracy between registries, with the highest accuracy in the registry that contributed the most data (Seattle Registry, BER ratios for all registries >1.25). BER showed no significant algorithmic bias in extracting biomarkers (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2) for race, Hispanic ethnicity, age at diagnosis, or socioeconomic subgroups (BER ratio <1.25). DP, EOD, and EOP all showed insignificant results. Discussion: We observed significant differences in BER by registry, but no significant bias using the DP, EOD, and EOP metrics for socio-demographic or racial categories. This highlights the importance of employing a diverse set of metrics for a comprehensive evaluation of model fairness. Conclusion: A thorough evaluation of algorithmic biases that may affect equality in clinical care is a critical step before deploying algorithms in the real world. We found little evidence of algorithmic bias in our biomarker classification tool. Artificial intelligence tools to expedite information extraction from clinical records could accelerate clinical trial matching and improve care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

BIN1 protein isoforms are differentially expressed in astrocytes, neurons, and microglia: neuronal and astrocyte BIN1 are implicated in tau pathology

Background: Identified as an Alzheimer’s disease (AD) susceptibility gene by genome wide-association studies, BIN1 has 10 isoforms that are expressed in the Central Nervous System (CNS). The distribution of these isoforms in different cell types, as well as their role in AD pathology still remains unclear. Methods: Utilizing antibodies targeting specific BIN1 epitopes in human post-mortem tissue and analyzing mRNA expression data from purified microglia, we identified three isoforms expressed in neurons and astrocytes (isoforms 1, 2 and 3) and four isoforms expressed in microglia (isoforms 6, 9, 10 and 12). The abundance of selected peptides, which correspond to groups of BIN1 protein isoforms, was measured in dorsolateral prefrontal cortex, and their relation to neuropathological features of AD was assessed. Results: Peptides contained in exon 7 of BIN1’s N-BAR domain were found to be significantly associated with ADrelated traits and, particularly, tau tangles. Decreased expression of BIN1 isoforms containing exon 7 is associated with greater accumulation of tangles and subsequent cognitive decline, with astrocytic rather than neuronal BIN1 being the more likely culprit. These effects are independent of the BIN1 AD risk variant. Conclusions: Exploring the molecular mechanisms of specific BIN1 isoforms expressed by astrocytes may open new avenues for modulating the accumulation of Tau pathology in AD. Keywords: BIN1 isoforms, Alzheimer’s disease, Amyloid, Tau, Microglia, Astrocytes, Neurons

Taga, Mariko↗
DOE OSTI2020

Using case-level context to classify cancer pathology reports

Individual electronic health records (EHRs) and clinical reports are often part of a larger sequence—for example, a single patient may generate multiple reports over the trajectory of a disease. In applications such as cancer pathology reports, it is necessary not only to extract information from individual reports, but also to capture aggregate information regarding the entire cancer case based off case-level context from all reports in the sequence. In this paper, we introduce a simple modular add-on for capturing case-level context that is designed to be compatible with most existing deep learning architectures for text classification on individual reports. We test our approach on a corpus of 431,433 cancer pathology reports, and we show that incorporating case-level context significantly boosts classification accuracy across six classification tasks—site, subsite, laterality, histology, behavior, and grade. We expect that with minimal modifications, our add-on can be applied towards a wide range of other clinical text-based tasks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Organic Matrix Derived from Host–Microbe Interplay Contributes to Pathological Renal Biomineralization

Matrix stones are a rare form of kidney stones. They feature a high percentage of hydrogel-like organic matter, and their formation is closely associated with urinary tract infections. Herein, comprehensive materials and biochemical approaches were taken to map the organic-inorganic interface and gather insights into the host-microbe interplay in pathological renal biomineralization. Surgically extracted soft and slimy matrix stones were examined using micro-X-ray computed tomography and various microspectroscopy techniques. Higher-mineral-density laminae were positive for calcium-bound Alizarin red. Lower-mineral-density laminae revealed periodic acid-Schiff-positive organic filamentous networks of varied thickness. These organic filamentous networks, which featured a high polysaccharide content, were enriched with zinc, carbon, and sulfur elements. Neutrophil extracellular traps (NETs) along with immune response-related proteins, including calprotectin, myeloperoxidase, CD63, and CD86, also were identified in the filamentous networks. Expressions of NETs and upregulation of polysaccharide-rich mucin secretion are proposed as a part of the host immune defense to "trap" pathogens. These host-microbe derived organic matrices can facilitate heterogeneous nucleation and precipitation of inorganic particulates, resulting in macroscale aggregates known as "matrix stones". These insights into the plausible aggregation of constituents through host-microbe interplay underscore the unique "double-edged sword" effect of the host immune response to pathogens and the resulting renal biominerals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Deep active learning for classifying cancer pathology reports

Abstract Background Automated text classification has many important applications in the clinical setting; however, obtaining labelled data for training machine learning and deep learning models is often difficult and expensive. Active learning techniques may mitigate this challenge by reducing the amount of labelled data required to effectively train a model. In this study, we analyze the effectiveness of 11 active learning algorithms on classifying subsite and histology from cancer pathology reports using a Convolutional Neural Network as the text classification model. Results We compare the performance of each active learning strategy using two differently sized datasets and two different classification tasks. Our results show that on all tasks and dataset sizes, all active learning strategies except diversity-sampling strategies outperformed random sampling, i.e., no active learning. On our large dataset (15K initial labelled samples, adding 15K additional labelled samples each iteration of active learning), there was no clear winner between the different active learning strategies. On our small dataset (1K initial labelled samples, adding 1K additional labelled samples each iteration of active learning), marginal and ratio uncertainty sampling performed better than all other active learning techniques. We found that compared to random sampling, active learning strongly helps performance on rare classes by focusing on underrepresented classes. Conclusions Active learning can save annotation cost by helping human annotators efficiently and intelligently select which samples to label. Our results show that a dataset constructed using effective active learning techniques requires less than half the amount of labelled data to achieve the same performance as a dataset constructed using random sampling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Global brain activity and its coupling with cerebrospinal fluid flow is related to tau pathology

Abstract INTRODUCTION Factors responsible for the deposition of pathological tau in the brain are incompletely understood. This study links macroscale tau deposition in the human brain to cerebrospinal fluid (CSF) flow dynamics using resting‐state functional magnetic resonance imaging (rsfMRI). METHODS Low‐frequency (< 0.1 Hz) resting‐state global brain activity is coupled with CSF flow and potentially reflects CSF dynamics‐related clearance. We examined the correlation between rsfMRI measures of CSF inflow and global activity (gBOLD–CSF coupling) as a predictor, interacting with amyloid beta (Aβ), of tau and cortical thickness (dependent variables) across Alzheimer's Disease Neuroimaging Initiative (ADNI) participants from cognitively unimpaired through mild cognitive impairment (MCI) and Alzheimer's disease (AD). RESULTS Tau deposition in Aβ+ participants, accompanied by cortical thinning and cognitive decline, is associated with decreased gBOLD–CSF coupling. Tau mediates the relationship between coupling and thickness. DISCUSSION Findings suggest that resting‐state global brain activity and CSF movements comodulate Alzheimer's tau deposition, presumably related to CSF clearance. Highlights A non‐invasive functional magnetic resonance imaging (fMRI) assessment of a CSF clearance‐related process is carried out. Global brain activity is coupled with CSF inflow in human fMRI during resting state. Global fMRI–CSF coupling is correlated with tau in Alzheimer's disease (AD). This coupling measure is also associated with cortical thickness, mediated by tau.

Neurosciences & Neurology↗
DOE OSTI2025

Cognitive aging outcomes are related to both tau pathology and maintenance of cingulate cortex structure

Abstract INTRODUCTION Successful cognitive aging is related to both maintaining brain structure and avoiding Alzheimer's disease (AD) pathology, but how these factors interplay is unclear. METHODS A total of 109 cognitively normal older adults (70+ years old) underwent amyloid beta (Aβ) and tau positron emission tomography (PET) imaging, structural magnetic resonance imaging (MRI), and cognitive testing. Cognitive aging was quantified using the cognitive age gap (CAG), subtracting chronological age from predicted cognitive age. RESULTS Lower CAG (younger cognitive age) was related to slower decline in episodic memory, multi‐domain cognition, and atrophy of the midcingulate cortex (MCC). Lower entorhinal cortical tau was linked to slower decline in episodic memory, multi‐domain cognition, and hippocampal atrophy. DISCUSSION These results suggest that aging outcomes may be influenced by two independent pathways: one associated with tau accumulation, affecting primarily memory and hippocampal atrophy, and another involving tau‐independent structural preservation of the MCC, benefiting multi‐domain cognition over time. Highlights Younger cognitive age (lower cognitive age gap [CAG]) is related to slower cognitive decline. Lower CAG is linked to slower midcingulate cortex (MCC) atrophy. Reduced tau in the entorhinal cortex is related to less hippocampal atrophy and cognitive decline. Structural preservation of the MCC benefits multi‐domain cognition over time. Two independent pathways influence cognitive aging: tau accumulation and MCC preservation.

Neurosciences & Neurology↗
DOE OSTI2021

Repetitive diacetyl vapor exposure promotes ubiquitin proteasome stress and precedes bronchiolitis obliterans pathology

Bronchiolitis obliterans (BO) is a devastating lung disease seen commonly after lung transplant but also seen following severe respiratory tract infection or chemical inhalation exposure. Diacetyl (DA; 2,3-butanedione), highly reactive alpha-diketone is known to cause BO when inhaled, however, the mechanisms of how inhalation exposure leads to BO development remains poorly understood. In the current work, we combined two clinically relevant models for studying the pathogenesis of DA-induced BO: (1) an in vivo rat model of repetitive DA vapor exposures with recovery and (2) an in vitro model of primary human airway epithelial cells exposed to pure DA vapors. Rats exposed to 5 consecutive days 200 parts-per-million DA 6 hrs per day had worsening survival, persistent hypoxemia, poor weight gain, and histologic evidence of BO 14 days after DA exposure cessation. At the end of exposure, increased expression of the ubiquitin stress protein, ubiquitin-C, accumulated within DA-exposed rat lung homogenates, localized primarily to the airway epithelium, the primary site of BO development, and did not occur in air-exposed controls. Lung proteasome activity increased concurrently after DA exposure. In primary human airway cultures, global proteomics analysis identified 519 significantly modified proteins in DA-exposed samples relative to controls with the ubiquitin proteasome system, endosomal reticulum transport, and the response to unfolded protein pathways being upregulated while cell-cell adhesion and oxidation-reduction pathways being downregulated in DA-exposed samples. Altogether, repetitive DA vapor exposure resulted in abundant protein damage, accumulation of polyubiquinated proteins, and ubiquitin proteasome stress prior to the development of chemical-induced BO pathology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Locus coeruleus catecholamines link neuroticism and vulnerability to tau pathology in aging

Higher neuroticism is a risk factor for Alzheimer's disease (AD), and is implicated in disordered stress responses. The locus coeruleus (LC)-catecholamine system is activated during perceived threat and is a centerpiece of developing models of the pathophysiology of AD, as it is the first brain region to develop abnormal tau. We examined relationships among the "Big 5" personality traits, LC catecholamine synthesis capacity measured with [ 18 F]Fluoro-m-tyrosine PET, and tau burden measured with [ 18 F]Flortaucipir PET in cognitively normal older adults (n = 47). β-amyloid (Aβ) status was determined using [ 11 C]Pittsburgh compound B PET (n = 14 Aβ positive). Lower LC catecholamine synthesis capacity was associated with higher neuroticism, more depressive symptoms as measured by the Geriatric Depression Scale, and higher amygdala tau-PET binding. Exploratory analyses with other personality traits revealed that low trait conscientiousness was also related to both lower LC catecholamine synthesis capacity, and more depressive symptoms. A significant indirect path linked both high neuroticism and low conscientiousness to greater amygdala tau burden via their mutual association with low LC catecholamine synthesis capacity. Together, these findings reveal LC catecholamine synthesis capacity to be a promising marker of affective health and pathology burden in aging, and identifies candidate neurobiological mechanisms for the effect of personality on increased vulnerability to dementia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Antibodies Raised Against an Aβ Oligomer Mimic Recognize Pathological Features in Alzheimer’s Disease and Associated Amyloid-Disease Brain Tissue

Antibodies that target the β-amyloid peptide (Aβ) and its associated assemblies are important tools in Alzheimer’s disease research and have emerged as promising Alzheimer’s disease therapies. This paper reports the creation and characterization of a triangular Aβ trimer mimic composed of Aβ 17–36 β-hairpins and the generation and study of polyclonal antibodies raised against the Aβ trimer mimic. The Aβ trimer mimic is covalently stabilized by three disulfide bonds at the corners of the triangular trimer to create a homogeneous oligomer. Structural, biophysical, and cell-based studies demonstrate that the Aβ trimer mimic shares characteristics with oligomers of full-length Aβ. X-ray crystallography elucidates the structure of the trimer and reveals that four copies of the trimer assemble to form a dodecamer. SDS-PAGE, size exclusion chromatography, and dynamic light scattering reveal that the trimer also forms higher-order assemblies in solution. Cell-based toxicity assays show that the trimer elicits LDH release, decreases ATP levels, and activates caspase-3/7 mediated apoptosis. Immunostaining studies on brain slices from people who lived with Alzheimer’s disease and people who lived with Down syndrome reveal that the polyclonal antibodies raised against the Aβ trimer mimic recognize pathological features including different types of Aβ plaques and cerebral amyloid angiopathy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

O-GlcNAc forces an α-synuclein amyloid strain with notably diminished seeding and pathology

Amyloid-forming proteins such α-synuclein and tau, which are implicated in Alzheimer’s and Parkinson’s disease, can form different fibril structures or strains with distinct toxic properties, seeding activities and pathology. Understanding the determinants contributing to the formation of different amyloid features could open new avenues for developing disease-specific diagnostics and therapies. Here we report that O-GlcNAc modification of α-synuclein monomers results in the formation of amyloid fibril with distinct core structure, as revealed by cryogenic electron microscopy, and diminished seeding activity in seeding-based neuronal and rodent models of Parkinson’s disease. Although the mechanisms underpinning the seeding neutralization activity of the O-GlcNAc-modified fibrils remain unclear, our in vitro mechanistic studies indicate that heat shock proteins interactions with O-GlcNAc fibril inhibit their seeding activity, suggesting that the O-GlcNAc modification may alter the interactome of the α-synuclein fibrils in ways that lead to reduce seeding activity in vivo. Our results show that posttranslational modifications, such as O-GlcNAc modification, of α-synuclein are key determinants of α-synuclein amyloid strains and pathogenicity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗