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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Advances in Medical Analytics Solutions for Autonomous Medical Operations on Long-Duration Missions

A review will be presented on the progress made under STMDGame Changing Development Program Funding towards the development of a Medical Decision Support System for augmenting crew capabilities during long-duration missions, such as Mars Transit. To create an MDSS, initial work requires acquiring images and developing models that analyze and assess the features in such medical biosensor images that support medical assessment of pathologies. For FY17, the project has focused on ultrasound images towards cardiac pathologies: namely, evaluation and assessment of pericardial effusion identification and discrimination from related pneumothorax and even bladder-induced infections that cause inflammation around the heart. This identification is substantially changed due to uncertainty due to conditions of fluid behavior under space-microgravity. This talk will present and discuss the work-to-date in this Project, recognizing conditions under which various machine learning technologies, deep-learning via convolutional neural nets, and statistical learning methods for feature identification and classification can be employed and conditioned to graphical format in preparation for attachment to an inference engine that eventually creates decision support recommendations to remote crew in a triage setting.

Medical Decision Support Systems↗
DOE OSTI2026

Identification of potent inhibitors of JUN N-terminal kinases for treatment of endometriosis and associated pain

Endometriosis, defined as the ectopic growth of endometrial tissue outside of the uterine cavity, is an inflammatory and hormone-dependent disease that causes excruciating pelvic pain, infertility, and significantly decreases quality of life in affected patients. The JUN N-terminal kinases (JNKs) are a leading class of nonhormonal therapeutic targets that have been validated in preclinical models of endometriosis and in a Phase 1/2 clinical trial. Despite their therapeutic potential, JNK inhibitors with increased potency and specificity are needed to address the inflammatory pathology of endometriosis and to prevent disease progression. Leveraging a DNA-encoded chemical library collection of ~4 billion compounds, we identified lead inhibitor CDD-2428 and optimized derivatives, CDD-2728 and CDD-3013, with excellent binding affinity to JNK1-3 (K d = 0.12 to 3.7 nM), enhanced selectivity, metabolic stability, and cellular permeability. Crystallographic and biochemical studies confirmed that CDD-3013 exhibited superior kinase selectivity with improved efficacy compared to existing JNK inhibitors. In primary endometriosis cell models, CDD-2728 and CDD-3013 suppressed JNK-dependent inflammatory signaling, dampening pathways linked to pain, invasion, angiogenesis, and macrophage recruitment. In an endometriosis mouse model, both CDD-2728 and CDD-3013 reduced endometriotic lesion size, macrophage infiltration, and cellular proliferation, showing in vivo efficacy. When tested in a lipopolysaccharide-induced hyperalgesia model, CDD-2728 and CDD-3013 decreased markers of induced pain, as measured by changes in a dynamic weight bearing test and Grimace scores. These findings nominate CDD-2728 and CDD-3013 as potent, nonhormonal therapeutic candidates for endometriosis with broad anti-inflammatory and analgesic activity, addressing a critical unmet clinical need.

Madasu, Chandrashekhar [Department of Pathology an↗
DOE OSTI2021

Connectivity‐based parcellation of normal and anatomically distorted human cerebral cortex

Abstract For over a century, neuroscientists have been working toward parcellating the human cortex into distinct neurobiological regions. Modern technologies offer many parcellation methods for healthy cortices acquired through magnetic resonance imaging. However, these methods are suboptimal for personalized neurosurgical application given that pathology and resection distort the cerebrum. We sought to overcome this problem by developing a novel connectivity‐based parcellation approach that can be applied at the single‐subject level. Utilizing normative diffusion data, we first developed a machine‐learning (ML) classifier to learn the typical structural connectivity patterns of healthy subjects. Specifically, the Glasser HCP atlas was utilized as a prior to calculate the streamline connectivity between each voxel and each parcel of the atlas. Using the resultant feature vector, we determined the parcel identity of each voxel in neurosurgical patients ( n = 40) and thereby iteratively adjusted the prior. This approach enabled us to create patient‐specific maps independent of brain shape and pathological distortion. The supervised ML classifier re‐parcellated an average of 2.65% of cortical voxels across a healthy dataset ( n = 178) and an average of 5.5% in neurosurgical patients. Our patient dataset consisted of subjects with supratentorial infiltrating gliomas operated on by the senior author who then assessed the validity and practical utility of the re‐parcellated diffusion data. We demonstrate a rapid and effective ML parcellation approach to parcellation of the human cortex during anatomical distortion. Our approach overcomes limitations of indiscriminately applying atlas‐based registration from healthy subjects by employing a voxel‐wise connectivity approach based on individual data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Perimatrix of middle ear cholesteatoma: A granulation tissue with a specific transcriptomic signature

Objectives/Hypothesis: To establish comprehensive transcriptomic profiles of cholesteatoma perimatrix tissue and granulation tissue from chronic otitis media (COM) that did not develop cholesteatoma, which can indicate molecular pathways involved in the cholesteatoma perimatrix pathology and invasiveness. Study Design: Retrospective Case Series. Methods: Transcriptome data were obtained from cholesteatoma perimatrix tissue and COM granulation tissue by an Illumina iScan microarray. Differentially expressed genes (DEGs) were subsequently analyzed using both bioinformatical functional annotation and network analysis. Expression of candidate genes (MMP9 and LCN2) was validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) on a larger group of samples. Results: Analysis of the transcriptome led to the identification of 169 differentially expressed genes between investigated tissues. Bioinformatic analysis suggested that most significant biological processes involving DEGs were previously described in cholesteatoma pathology. Network analysis identified ERBB2, TFAP2A, and TP63 as major hubs of the DEGs molecular network. Furthermore, it was observed that the cellular component most significantly enriched in DEGs was extracellular space containing 47 DEGs. Using qRT-PCR, it was confirmed that mRNA levels of the major extracellular hub (MMP9) are increased, whereas its interacting molecule (LCN2) mRNA levels were decreased in cholesteatoma perimatrix tissue compared to COM granulation tissue. Conclusions: The current study approach offers an overall look at molecular mechanisms that describe the cholesteatoma entity by focusing exclusively on the perimatrix processes in comparison to COM granulation tissue. The observed differences in gene expression between cholesteatoma perimatrix and COM granulation tissue could suggest novel markers potentially influenced by the perimatrix–matrix molecular interplay, which is not present in COM without cholesteatoma. Level of Evidence: NA. Laryngoscope, 130:E220–E227, 2020. © 2019 The American Laryngological, Rhinological and Otological Society, Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Deformable phrase level attention: A flexible approach for improving AI based medical coding

Objective: Improving the AI-driven automated medical encoding of clinical text plays a vital role in gathering information on the occurrence of diseases to improve population-level health. This work presents a novel attention mechanism designed to enhance text classification models and ensure appropriate classification of medical concepts in unstructured electronic health records. Materials and Methods: We developed a deformable, phrase-level attention mechanism to identify important lexical word-level and contextual phrase-level information from clinical text documents. We evaluated conventional and transformer-based deep learning models that we extended with our attention mechanism on the extraction of critical cancer information (e.g., site, subsite, laterality, histology, behavior) from 629,908 electronic pathology reports and on the automated medical encoding of 52,722 hospital discharge summaries. Results: Transformer-based models with the deformable, phrase-level attention mechanism achieved the best performance on the extraction of critical cancer information from pathology reports. Conventional- and transformer-based models show similar or better performance than their baseline counterparts on the automated medical encoding of clinical documents. Discussion: The addition of phrase-level information allowed models extended with our proposed method to outperform standard word-level attention. Our method showed favorable properties for the real-world application in terms of model robustness and phenotyping. These results indicate that our method is promising for automated data harmonization for common data models. Conclusion: This work proposes a novel deformable, phrase-level attention mechanism that enhances text classification models in the extraction of medical concepts from clinical text documents. We demonstrate strong performances on two clinical text datasets and showcase real-world deployability of our method.

Automated medical encoding↗
DOE OSTI2020

Integrated Proteomic and Glycoproteomic Characterization of Human High-Grade Serous Ovarian Carcinoma

Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potentialroles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters.

Hu, Yingwei↗
DOE OSTI2021

Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types

In the last decade, the widespread adoption of electronic health record documentation has created huge opportunities for information mining. Natural language processing (NLP) techniques using machine and deep learning are becoming increasingly widespread for information extraction tasks from unstructured clinical notes. Disparities in performance when deploying machine learning models in the real world have recently received considerable attention. In the clinical NLP domain, the robustness of convolutional neural networks (CNNs) for classifying cancer pathology reports under natural distribution shifts remains understudied. In this research, we aim to quantify and improve the performance of the CNN for text classification on out-of-distribution (OOD) datasets resulting from the natural evolution of clinical text in pathology reports. We identified class imbalance due to different prevalence of cancer types as one of the sources of performance drop and analyzed the impact of previous methods for addressing class imbalance when deploying models in real-world domains. Our results show that our novel class-specialized ensemble technique outperforms other methods for the classification of rare cancer types in terms of macro F1 scores. We also found that traditional ensemble methods perform better in top classes, leading to higher micro F1 scores. Based on our findings, we formulate a series of recommendations for other ML practitioners on how to build robust models with extremely imbalanced datasets in biomedical NLP applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Spatial Glycomics and Kidney Disease

Glycans are critical for the kidney's physiological and pathological cellular functions, and our ability to reveal their spatial distributions within tissues has helped us reveal how these carbohydrate moieties are involved in many of these processes. This review discusses the role of different types of glycans in kidney biology and disease, common approaches used for glycan imaging, and how glycan imaging has helped us better understand kidney pathology. Here, we mainly focus on emerging methods using mass spectrometry imaging (MSI) because this technology is untargeted and provides complete information on glycan composition compared to the other methods, such as lectin and metabolite labeling, which are targeted and often inform only on the specific part of a glycan structure. We especially focus on protein N-glycosylation, as this is one of the most common post-translational modifications, and these moieties play a vital role in renal structure and function. The recent advancements in MSI of N-glycans we reviewed have provided new insights into the pathophysiology of the kidney and paved the way for clinical application.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Deep learning integrates histopathology and proteogenomics at a pan-cancer level

We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Lymphocytic microparticles suppress retinal angiogenesis via targeting Müller cells in the ischemic retinopathy mouse model

Highlights: F0B7 • LMPs possess strong angiogenesis-inhibiting properties. F0B7 • LMPs suppress Müller cell-derived angiogenic/chemoattractant factors. F0B7 • LMPs attenuate pathological retinal NV and the infiltration of macrophages in vivo. F0B7 • LMPs downregulate ERK1/2 and HIF-1α both in vitro and in vivo. Retinopathy of prematurity (ROP) is the primary cause of visual impairment and vision loss in premature infants, which results from the formation of aberrant retinal neovascularization (NV). An emerging body of evidence has shown that Müller cells are the predominant source of vascular endothelial growth factor (VEGF), which also serves as a chemoattractant for monocyte/macrophage lineage. The recruitment of macrophages is increased during retinal NV, and they exert a pro-angiogenic role in ROP. We have shown that lymphocytic microparticles (microvesicles; LMPs) derived from apoptotic human T lymphocytes possess strong angiogenesis-inhibiting properties. Here, we investigated the effect of LMPs on the chemotactic capacity of Müller cells in vitro using rat Müller cell rMC-1 and mouse macrophage RAW 264.7. In addition, the impact of LMPs was determined in vivo using a mouse model of oxygen-induced ischemic retinopathy (OIR). The results revealed that LMPs were internalized by rMC-1 and reduced their cell proliferation dose-dependently without inducing cell apoptosis. LMPs inhibited the chemotactic capacity of rMC-1 on RAW 264.7 via reducing the expression of VEGF. Moreover, LMPs attenuated pathological retinal NV and the infiltration of macrophages in vivo. LMPs downregulated ERK1/2 and HIF-1α both in vitro and in vivo. These findings expand our understanding of the effects of LMPs, providing evidence of LMPs as a promising therapeutic approach for the treatment of retinal NV diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Evaluation of Copper Chelation Therapy in a Transgenic Rat Model of Cerebral Amyloid Angiopathy

Cerebral amyloid angiopathy (CAA) is characterized by the accumulation of the amyloid β (Aβ) protein in blood vessels and leads to hemorrhages, strokes, and dementia in elderly individuals. Recent reports have shown elevated copper levels colocalized with vascular amyloid in human CAA and Alzheimer’s disease patients, which have been suggested to contribute to cytotoxicity through the formation of reactive oxygen species. Here, we treated a transgenic rat model of CAA (rTg-DI) with the copper-specific chelator, tetrathiomolybdate (TTM), via intraperitoneal (IP) administration for 6 months to determine if it could lower copper content in vascular amyloid deposits and modify CAA pathology. In this work, results showed that TTM treatment led to elevated Aβ load in the hippocampus of the rTg-DI rats and increased microbleeds in the wild type (WT) animals. X-ray fluorescence microscopy was performed to image the distribution of copper and revealed a surprising increase in copper colocalized with Aβ aggregates in TTM-treated rTg-DI rats. Unexpectedly, we also found an increase in the copper content in unaffected vessels of both rTg-DI and WT animals. These results show that IP administration of TTM was ineffective in removing copper from vascular Aβ aggregates in vivo and increased the development of disease pathology in CAA.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Transcription Factor 4 loss-of-function is associated with deficits in progenitor proliferation and cortical neuron content

Transcription Factor 4 ( TCF4) has been associated with autism, schizophrenia, and other neuropsychiatric disorders. However, how pathological TCF4 mutations affect the human neural tissue is poorly understood. Here, we derive neural progenitor cells, neurons, and brain organoids from skin fibroblasts obtained from children with Pitt-Hopkins Syndrome carrying clinically relevant mutations in TCF4 . We show that neural progenitors bearing these mutations have reduced proliferation and impaired capacity to differentiate into neurons. We identify a mechanism through which TCF4 loss-of-function leads to decreased Wnt signaling and then to diminished expression of SOX genes, culminating in reduced progenitor proliferation in vitro. Moreover, we show reduced cortical neuron content and impaired electrical activity in the patient-derived organoids, phenotypes that were rescued after correction of TCF4 expression or by pharmacological modulation of Wnt signaling. This work delineates pathological mechanisms in neural cells harboring TCF4 mutations and provides a potential target for therapeutic strategies for genetic disorders associated with this gene.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Quantitative X-ray tomographic analysis reveals calcium precipitation in cataractogenesis

Cataracts, named for pathological light scattering in the lens, are known to be associated with increased large protein aggregates, disrupted protein phase separation, and/or osmotic imbalances in lens cells. We have applied synchrotron phase contrast X-ray micro-computed tomography to directly examine an age-related nuclear cataract model in Cx46 knockout (Cx46KO) mice. High-resolution 3D X-ray tomographic images reveal amorphous spots and strip-like dense matter precipitates in lens cores of all examined Cx46KO mice at different ages. The precipitates are predominantly accumulated in the anterior suture regions of lens cores, and they become longer and dense as mice age. Alizarin red staining data confirms the presence of calcium precipitates in lens cores of all Cx46KO mice. This study indicates that the spatial and temporal calcium precipitation is an age-related event associated with age-related nuclear cataract formation in Cx46KO mice, and further suggests that the loss of Cx46 promotes calcium precipitates in the lens core, which is a new mechanism that likely contributes to the pathological light scattering in this age-related cataract model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Chromatin structure predicts survival in glioma patients

The pathological changes in epigenetics and gene regulation that accompany the progression of low-grade to high-grade gliomas are under-studied. The authors use a large set of paired atac-seq and RNA-seq data from surgically resected glioma specimens to infer gene regulatory relationships in glioma. Thirty-eight glioma patient samples underwent atac-seq sequencing and 16 samples underwent additional RNA-seq analysis. Using an atac-seq/RNA-seq correlation matrix, atac-seq peaks were paired with genes based on high correlation values (|r 2 | > 0.6). Samples clustered by IDH1 status but not by grade. Surprisingly there was a trend for IDH1 mutant samples to have more peaks. The majority of peaks are positively correlated with survival and positively correlated with gene expression. Constructing a model of the top six atac-seq peaks created a highly accurate survival prediction model (r 2 = 0.68). Four of these peaks were still significant after controlling for age, grade, pathology, IDH1 status and gender. Grade II, III, and IV (primary) samples have similar transcription factors and gene modules. However, grade IV (recurrent) samples have strikingly few peaks. Patient-derived glioma cultures showed decreased peak counts following radiation indicating that this may be radiation-induced. This study supports the notion that IDH1 mutant and IDH1 wildtype gliomas have different epigenetic landscapes and that accessible chromatin sites mapped by atac-seq peaks tend to be positively correlated with expression. The data in this study leads to a new model of treatment response wherein glioma cells respond to radiation therapy by closing open regions of DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection

Abstract The emergence of the novel SARS-CoV-2 virus is the most important public-health issue of our time. Understanding the diverse clinical presentations of the ensuing disease, COVID-19, remains a critical unmet need. Here we present a comprehensive listing of the diverse clinical indications associated with COVID-19. We explore the theory that anti-SARS-CoV-2 antibodies could cross-react with endogenous human proteins driving some of the pathologies associated with COVID-19. We describe a novel computational approach to estimate structural homology between SARS-CoV-2 proteins and human proteins. Antibodies are more likely to interrogate 3D-structural epitopes than continuous linear epitopes. This computational workflow identified 346 human proteins containing a domain with high structural homology to a SARS-CoV-2 Wuhan strain protein. Of these, 102 proteins exhibit functions that could contribute to COVID-19 clinical pathologies. We present a testable hypothesis to delineate unexplained clinical observations vis-à-vis COVID-19 and a tool to evaluate the safety-risk profile of potential COVID-19 therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

RhoA and vigilin are candidates for immunohistochemical markers for epithelioid malignant mesothelioma

Diagnostic markers of malignant mesothelioma (MM) have been extensively investigated. Immunohistochemistry (IHC) markers, such as calretinin, have been used for pathologic diagnosis. However, more diagnostic markers are required to improve the specificity and sensitivity of pathologic diagnosis. This study proposed two proteins as diagnostic markers for epithelioid MM. One is RhoA, an MM mutation-susceptible locus-derived protein, and another is vigilin, a lung small cell carcinoma marker. IHC was performed using 93 MM (epithelioid, 71 cases; sarcomatoid, 13 cases; and biphasic, 9 cases), 64 lung adenocarcinoma (LAC), 60 lung squamous cell carcinoma (LSC), and 14 normal mesothelial (NM) tissues. The majority of epithelioid MM cases were positive for both RhoA and vigilin, whereas both IHCs showed lower stainability in biphasic and sarcomatoid MM. Besides, both IHCs showed significantly higher stainability for RhoA and vigilin in epithelioid MM than in LAC and LSC (p < 0.05). Chi-square tests showed that both RhoA and vigilin IHC positive rate in epithelioid MM was not significantly different from that of calretinin (p > 0.05). In the differential diagnosis of MM from lung cancer, the accuracy and specificity of RhoA, vigilin, and calretinin staining were almost equivalent. Further, H-score test showed that there was no significant difference between RhoA versus calretinin and vigilin versus calretinin in IHC positivity in epithelioid MM (p > 0.05). In conclusion, RhoA and vigilin may be candidates for immunohistochemical markers for epithelioid MM.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Cdk5 mediates rotational force-induced brain injury

Abstract Millions of traumatic brain injuries (TBIs) occur annually. TBIs commonly result from falls, traffic accidents, and sports-related injuries, all of which involve rotational acceleration/deceleration of the brain. During these injuries, the brain endures a multitude of primary insults including compression of brain tissue, damaged vasculature, and diffuse axonal injury. All of these deleterious effects can contribute to secondary brain ischemia, cellular death, and neuroinflammation that progress for weeks, months, and lifetime after injury. While the linear effects of head trauma have been extensively modeled, less is known about how rotational injuries mediate neuronal damage following injury. Here, we developed a new model of repetitive rotational head trauma in rodents and demonstrated acute and prolonged pathological, behavioral, and electrophysiological effects of rotational TBI (rTBI). We identify aberrant Cyclin-dependent kinase 5 (Cdk5) activity as a principal mediator of rTBI. We utilized Cdk5-enriched phosphoproteomics to uncover potential downstream mediators of rTBI and show pharmacological inhibition of Cdk5 reduces the cognitive and pathological consequences of injury. These studies contribute meaningfully to our understanding of the mechanisms of rTBI and how they may be effectively treated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The flavonoid procyanidin C1 has senotherapeutic activity and increases lifespan in mice

Ageing-associated functional decline of organs and increased risk for age-related chronic pathologies is driven in part by the accumulation of senescent cells, which develop the senescence-associated secretory phenotype (SASP). Here we show that procyanidin C1 (PCC1), a polyphenolic component of grape seed extract (GSE), increases the healthspan and lifespan of mice through its action on senescent cells. By screening a library of natural products, we find that GSE, and PCC1 as one of its active components, have specific effects on senescent cells. At low concentrations, PCC1 appears to inhibit SASP formation, whereas it selectively kills senescent cells at higher concentrations, possibly by promoting production of reactive oxygen species and mitochondrial dysfunction. In rodent models, PCC1 depletes senescent cells in a treatment-damaged tumour microenvironment and enhances therapeutic efficacy when co-administered with chemotherapy. Intermittent administration of PCC1 to either irradiated, senescent cell-implanted or naturally aged old mice alleviates physical dysfunction and prolongs survival. We identify PCC1 as a natural senotherapeutic agent with in vivo activity and high potential for further development as a clinical intervention to delay, alleviate or prevent age-related pathologies.

60 APPLIED LIFE SCIENCES↗