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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 OSTI2012

Fibroblast Growth Factor 2-A Predictor of Outcome for Patients Irradiated for Stage II-III Non-Small-Cell Lung Cancer

Purpose: The prognostic value of the tumor cell expression of the fibroblast growth factor 2 (FGF-2) in patients with non-small-cell lung cancer (NSCLC) is unclear. The present study investigated the effect of tumor cell expression of FGF-2 on the outcome of 60 patients irradiated for Stage II-III NSCLC. Methods and Materials: The effect of FGF-2 expression and 13 additional factors on locoregional control (LRC), metastasis-free survival (MFS), and overall survival (OS) were retrospectively evaluated. These additional factors included age, gender, Karnofsky performance status, histologic type, histologic grade, T and N category, American Joint Committee on Cancer stage, surgery, chemotherapy, pack-years, smoking during radiotherapy, and hemoglobin during radiotherapy. Locoregional failure was identified by endoscopy or computed tomography. Univariate analyses were performed with the Kaplan-Meier method and the Wilcoxon test and multivariate analyses with the Cox proportional hazard model. Results: On univariate analysis, improved LRC was associated with surgery (p = .017), greater hemoglobin levels (p = .036), and FGF-2 negativity (p <.001). On multivariate analysis of LRC, surgery (relative risk [RR], 2.44; p = .037), and FGF-2 expression (RR, 5.06; p <.001) maintained significance. On univariate analysis, improved MFS was associated with squamous cell carcinoma (p = .020), greater hemoglobin levels (p = .007), and FGF-2 negativity (p = .001). On multivariate analysis of MFS, the hemoglobin levels (RR, 2.65; p = .019) and FGF-2 expression (RR, 3.05; p = .004) were significant. On univariate analysis, improved OS was associated with a lower N category (p = .048), greater hemoglobin levels (p <.001), and FGF-2 negativity (p <.001). On multivariate analysis of OS, greater hemoglobin levels (RR, 4.62; p = .002) and FGF-2 expression (RR, 3.25; p = .002) maintained significance. Conclusions: Tumor cell expression of FGF-2 appeared to be an independent negative predictor of LRC, MFS, and OS.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2011

Multivariate statistics applications in scanning transmission electron microscopy X-ray spectrum imaging

A modern scanning transmission electron microscope (STEM) fitted with an energy dispersive X-ray spectroscopy (EDS) system can quickly and easily produce spectrum image (SI) datasets containing so much information (hundreds to thousands of megabytes) that they cannot be comprehensively interrogated by a human analyst. Therefore, advanced mathematical techniques are needed to glean materials science and engineering insight into the processing-structure-properties relationship of the examined material from the SI data. This review will discuss recent advances in the application of multivariate statistical analysis (MVSA) methods to STEM-EDS SI experiments. In particular, the fundamental mathematics of principal component analysis (PCA) and related methods are reviewed, and advanced methods such as multivariate curve resolution (MCR) are discussed. The applications of PCA and MCR-based techniques to solve difficult materials science problems, such as the analysis of a particle fully embedded in a matrix phase are discussed, as well as confounding effects such as rank deficiency that can confuse the results of MVSA computations. Possible future advances and areas in need of study are also mentioned.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

GMT: A deep learning approach to generalized multivariate translation for scientific data analysis and visualization

In scientific visualization, despite the significant advances of deep learning for data generation, researchers have not thoroughly investigated the issue of data translation. We present a new deep learning approach called generalized multivariate translation (GMT) for multivariate time-varying data analysis and visualization. Like V2V, GMT assumes a preprocessing step that selects suitable variables for translation. However, unlike V2V, which only handles one-to-one variable translation during training and inference, GMT enables one-to-many and many-to-many variable translation in the same framework. We leverage the recent StarGAN design from multi-domain image-to-image translation to achieve this generalization capability. We experiment with different loss functions and injection strategies to explore the best choices and leverage pre-training for performance improvement. We compare GMT with other state-of-the-art methods (i.e., Pix2Pix, V2V, StarGAN). Furthermore, the results demonstrate the overall advantage of GMT in translation quality and generalization ability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Microvascular invasion and grading in hepatocellular carcinoma: correlation with major and ancillary features according to LIRADS

Purpose: To assess major and ancillary parameters that could be correlated with Microvascular Invasion (MIV) and with histologic grade of HCC. Materials and methods: In this retrospective study, we assessed 62 patients (14 women–48 men; mean age, 63 years; range 38–80 years) that underwent hepatic resection for HCC. All patients were subject to Multidetector computed tomography (MDCT); 40 to Magnetic Resonance (MR) study. The radiologist assessed major and ancillary features according to LIRADS (v. 2018) and reported any radiological accessory findings if detected. Results: No major feature showed statistically significant differences and correlation with grading. Mean ADC value was correlated with grading and with MIV status. No major feature was correlated to MIV; progressive contrast enhancement and satellite nodules showed statistically different percentages with respect to the presence of MIV, so as at the monovariate correlation analysis, satellite nodules were correlated with the presence of MIV. At multivariate regression analysis, no factor proved to be strong predictors of grading while progressive contrast enhancement and satellite nodules were significantly associated with the MIV. Conclusion: Mean ADC value is correlated to HCC grading and MIV status. Progressive contrast enhancement and the presence of satellite nodules are correlated to MIV status.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Method for factor analysis of GC/MS data

The method of the present invention provides a fast, robust, and automated multivariate statistical analysis of gas chromatography/mass spectroscopy (GC/MS) data sets. The method can involve systematic elimination of undesired, saturated peak masses to yield data that follow a linear, additive model. The cleaned data can then be subjected to a combination of PCA and orthogonal factor rotation followed by refinement with MCR-ALS to yield highly interpretable results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system that allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Serum Gamma-Glutamyl-Transferase Independently Predicts Outcome After Transarterial Chemoembolization of Hepatocellular Carcinoma: External Validation

Purpose: An Asian study showed that gamma glutamyl transpeptidase (GGT) can predict survival after transarterial chemoembolization (TACE) of hepatocellular carcinoma (HCC). This study was designed to validate in a European population this biomarker as an independent predictor of outcome after TACE of HCC and to determine a threshold value for clinical use. Methods: In 88 consecutive patients treated by TACE for HCC, the optimal threshold for GGT serum level was determined by a ROC analysis. Endpoints were time-to-treatment failure (TTTF) and overall survival (OS). All multivariate models were internally validated using bootstrapping (90 replications). Results: Median follow-up lasted 373 days, and median overall survival was 748 days. The optimal threshold for GGT was 165 U/L (sensitivity: 89.3%; specificity: 56.7%; area under the ROC curve: 0.7515). Median TTTF was shorter when GGT was {>=}165 U/L (281 days vs. 850 days; P < 0.001). GGT {>=}165 U/L (hazard ratio (HR) = 2.06; P = 0.02), WHO PS of 2 (HR = 5.4; P = 0.002), and tumor size (HR = 1.12; P = 0.014) were independently associated with shorter TTTF. Median OS was shorter when GGT was {>=}165 U/L (508 days vs. not reached; P < 0.001). GGT {>=} 165 U/L (HR = 3.05; P = 0.029), WHO PS of 2 (HR = 12.95; P < 0.001), alfa-fetoprotein (HR = 2.9; P = 0.01), and tumor size (HR = 1.096; P = 0.013) were independently associated with shorter OS. The results were confirmed by bootstrapping. Conclusions: Our results provide in a European population the external validation of GGT as an independent predictor of outcome after TACE of HCC. A serum level of GGT {>=} 165 U/L is independently associated with both shorter TTTF and OS.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Leveraging visible and near-infrared spectroelectrochemistry to calibrate a robust model for Vanadium(IV/V) in varying nitric acid and temperature levels

Spectroelectrochemistry and optimal design of experiments can be used to rapidly build accurate models for species quantification and enable a greater level of process awareness. Optical spectroscopy can provide vital elemental and molecular information, but several hurdles must be overcome before it can become a widely adopted analytical method for remote analysis in the nuclear field. Analytes with varying oxidation state, acid concentration, and fluctuating temperature must be efficiently accounted for to minimize time and resources in restrictive hot cell environments. The classic one-factor-at-a-time approach is not suitable for frequent calibration/maintenance operations in this setting. Therefore, a novel alternative was developed to characterize a system containing vanadium(IV/V) (0.01–0.1 M), nitric acid (0.1–4 M), and varying temperatures (20–45 °C). Here, spectroelectrochemistry methods were used to acquire a sample set selected by optimal design of experiments. This new approach allows for the accurate analysis of vanadium and HNO 3 concentration by leveraging UV–Vis–NIR absorption spectroscopy with robust and accurate chemometric models. The top model's root mean squared error of prediction percent values were 3.47%, 4.06%, 3.40%, and 10.9% for V(IV), V(V), HNO 3 , and temperature, respectively. These models, efficiently developed using the designed approach, exhibited strong predictive accuracy for vanadium and acid with varying oxidation states and temperature using only spectrophotometry, which advances current technology for real-world hot cell applications. Additionally, Nernstian analysis of the V(IV/V) standard potential was performed using traditional absorbance methods and multivariate curve resolution (MCR). The successful tests demonstrated that MCR Nernst tests may be valuable in highly convoluted spectral systems to better understand the redox processes' behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Stereotactic Body Radiation Therapy for Spinal Metastases in the Postoperative Setting: A Secondary Analysis of Mature Phase 1-2 Trials

Purpose: To evaluate the outcomes in patients treated on prospective phase 1-2 protocols with postoperative stereotactic body radiation therapy (SBRT) and identify the associated prognostic variables. Methods and Materials: Sixty-six patients with 69 tumors were treated with SBRT on prospective phase 1-2 studies for spinal metastases between 2002 and 2010. All patients underwent SBRT after spine surgery, which included laminectomy, vertebrectomy, or a combination of these techniques. Renal cell carcinoma was the most common histology represented (n=35, 53%) followed by sarcomas (n=13, 20%). Thirty-one patients (47%) were treated with prior conventional radiation to the spine (median dose 30 Gy). Patients were followed up with spinal magnetic resonance imaging (MRI) studies to determine the treated tumor control (TC). Pain and other symptom data were collected prospectively to determine treatment response and toxicity. Results: The median follow-up time was 30 months (range, 1-145 months) for all patients and 75 months for living patients (range, 6-145 months). The actuarial 1-year rate of TC was 85%, adjacent vertebral body control was 85%, and overall survival (OS) was 74% (median 29 months). On multivariate competing-risks analysis, sarcoma histology (subhazard ratio [SHR] = 2.38, 95% confidence interval [CI] 1.05-5.6, P=.04) and larger preoperative tumor volumes (SHR=1.01, 95% CI 1.0-1.01, P=.006) were significantly associated with worse TC. Karnofsky performance status was the only significant predictor for OS on multivariate analysis. There were no differences in TC between patients treated with different surgical techniques or different preoperative or postoperative Bilsky grades. There were no grade 3 or higher neurologic toxicities. Conclusion: This study represents a large series of prospective data available on patients treated with SBRT in the postoperative setting. The combination of surgery with SBRT can offer patients with metastatic disease to the spine the chance of durable tumor control with minimal toxicity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Hypopharyngeal Dose Is Associated With Severe Late Toxicity in Locally Advanced Head-and-Neck Cancer: An RTOG Analysis

Purpose: Concurrent chemoradiation therapy (CCRT) for squamous cell carcinoma of the head and neck (SCCHN) increases local tumor control but at the expense of increased toxicity. We recently showed that several clinical/pretreatment factors were associated with the occurrence of severe late toxicity. This study evaluated the potential relationship between radiation dose delivered to the pharyngeal wall and toxicity. Methods and Materials: This was an analysis of long-term survivors from 3 previously reported Radiation Therapy Oncology Group (RTOG) trials of CCRT for locally advanced SCCHN (RTOG trials 91-11, 97-03, and 99-14). Severe late toxicity was defined in this secondary analysis as chronic grade 3-4 pharyngeal/laryngeal toxicity and/or requirement for a feeding tube {>=}2 years after registration and/or potential treatment-related death (eg, pneumonia) within 3 years. Radiation dosimetry (2-dimensional) analysis was performed centrally at RTOG headquarters to estimate doses to 4 regions of interest along the pharyngeal wall (superior oropharynx, inferior oropharynx, superior hypopharynx, and inferior hypopharynx). Case-control analysis was performed with a multivariate logistic regression model that included pretreatment and treatment potential factors. Results: A total of 154 patients were evaluable for this analysis, 71 cases (patients with severe late toxicities) and 83 controls; thus, 46% of evaluable patients had a severe late toxicity. On multivariate analysis, significant variables correlated with the development of severe late toxicity, including older age (odds ratio, 1.062 per year; P=.0021) and radiation dose received by the inferior hypopharynx (odds ratio, 1.023 per Gy; P=.016). The subgroup of patients receiving {<=}60 Gy to the inferior hypopharynx had a 40% rate of severe late toxicity compared with 56% for patients receiving >60 Gy. Oropharyngeal dose was not associated with this outcome. Conclusions: Severe late toxicity following CCRT is common in long-term survivors. Age is the most significant factor, but hypopharyngeal dose also was associated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Pregnancy outcome after first trimester exposure to domperidone—An observational cohort study

Abstract Aim To assess the teratogenic risk of domperidone by comparing the incidence of major malformation with domperidone to a control. Methods Pregnancy outcome data were obtained for women at two Japanese facilities that provide counseling on drug use during pregnancy between April 1988 and December 2017. The incidence of major malformation was calculated among infants born to women taking domperidone ( n = 519), nonteratogenic drugs (control, n = 1673), or metoclopramide (reference, n = 241) during the first trimester of pregnancy. Using the control group as reference, the crude odds ratio (OR) of the incidence of major malformation in the domperidone and metoclopramide groups was calculated using univariable logistic regression analysis. Adjusted OR was also calculated using multivariable logistic regression analysis adjusted for various other factors. Results The incidence of major malformation was 2.9% (14/485, 95% confidence interval [CI]: 1.6–4.8) in the domperidone group, 1.7% (27/1554, 95%CI: 1.1–2.5) in the control group, and 3.6% (8/224, 95%CI: 1.6–6.9) in the metoclopramide group. The adjusted multivariable logistic regression analysis showed no significant difference in incidence between the control and domperidone groups (adjusted OR: 1.86 [95%CI: 0.73–4.70], p = 0.191) or between the control and metoclopramide groups (adjusted OR: 2.20 [95%CI: 0.69–6.98], p = 0.183). Conclusions This observational cohort study showed that domperidone exposure during the first trimester was not associated with increased risk of major malformation in infants. These results may help alleviate the anxiety of patients who took domperidone during pregnancy.

Hishinuma, Kayoko↗
DOE OSTI2010

Methods for spectral image analysis by exploiting spatial simplicity

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Keenan, Michael R↗
DOE OSTI2020

Temporal Analysis and Scene Change Detection in Multispectral Overhead Imagery

Scene change detection can be a tedious and time consuming process especially when concerning large geographical areas, and the process can be even more cumbersome when analyzing changes in an area over large spans of time. Developing a useful way to help analysts recognize at what points in time significant changes to a scene have occurred can allow them to better focus their efforts in characterizing events. Applications include: Facility monitoring, Construction chronology, Monitoring of vehicle/aircraft activity, Characterization of larger sequences of events. In large areas exceeding hundreds to thousands of square kilometers in size, it can be difficult localizing when scene changes have occurred. Analysts can spend hours going through imagery to try to identify new construction, monitor facility activities, monitor vehicle movement, etc. where the object of interest may only be a few square meters. Our goal is to help cut down this time by giving analysts change maps with hot spots of change, allowing them to focus on regions that have experienced actual change in time frames they're interested in. Additionally, by combining these change maps into layers within a data cube, analysts can examine the change maps from a temporal perspective, allowing events to be characterized over spans of time. By opening the data cube in an imaging software capable of separating the layers, we can analyze the change maps sequentially, allowing us to examine scene changes occurring over time. As an example, we examined overhead imagery from Planet Labs of what appears to be a parking lot on Fort Irwin over the course of a year using ENVI, a geospatial satellite imagery analysis software. Using ENVI, we generate a graph of changes over time, and notice a particular segment near the end of our analysis window where no changes are detected. Examination of the actual satellite imagery reveals that during this time span, the parking lot was empty. This could be due to facility shutdown for maintenance or upgrades, or possibly even total workforce/vehicle fleet movement. Information like this could help analysts better characterize events, as well as to help create clearer timelines in larger sequences of events. Workflow steps: - Collect multiple maps of the same AOI (Area of Interest) during a time span of interest; - Generate change maps from AOI maps; - Generate data cube from change maps. An analyst can use the data cube to help inspect an AOI for activities within a time span of interest. If an event of interest is discovered, the analyst can then refer to the maps corresponding to the appropriate dates and times in the data cube to see precisely what is transpiring. The biggest objective being worked on is improving the change detection methodology employed. We currently use PCA-EM (Principal Component Analysis with Expectation Maximization), but we are currently focusing on implementing IR-MAD (Iteratively Reweighted Multivariate Alteration Detection) to be used in conjunction with PCA-EM in an effort to decrease false positivity and noise in the change maps we generate.

42 ENGINEERING↗
DOE OSTI2018

Part 2: Forensic attribution profiling of Russian VX in food using liquid chromatography-mass spectrometry

This work is part two of a three-part series in this issue of a Sweden-United States collaborative effort towards the understanding of the chemical attribution signatures of Russian VX (VR) in synthesized samples and complex food matrices. We describe the sourcing of VR present in food based on chemical analysis of attribution signatures by liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with multivariate data analysis. Analytical data was acquired from seven different foods spiked with VR batches that were synthesized via six different routes in two separate laboratories. The synthesis products were spiked at a lethal dose into seven food matrices: water, orange juice, apple purée, baby food, pea purée, liquid eggs and hot dog. After acetonitrile sample extraction, the samples were analyzed by LC-MS/MS operated in MRM mode. A multivariate statistical calibration model was built on the chemical attribution profiles from 118 VR spiked food samples. Using the model, an external test-set of the six synthesis routes employed for VR production was correctly identified with no observable major impact of the food matrices to the classification. The overall performance of the statistical models was found to be exceptional (94%) for the test set samples retrospectively classified to their synthesis routes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Risk of Cerebrovascular Events in Elderly Patients After Radiation Therapy Versus Surgery for Early-Stage Glottic Cancer

Purpose: Comprehensive neck radiation therapy (RT) has been shown to increase cerebrovascular disease (CVD) risk in advanced-stage head-and-neck cancer. We assessed whether more limited neck RT used for early-stage (T1-T2 N0) glottic cancer is associated with increased CVD risk, using the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database. Methods and Materials: We identified patients ≥66 years of age with early-stage glottic laryngeal cancer from SEER diagnosed from 1992 to 2007. Patients treated with combined surgery and RT were excluded. Medicare CPT codes for carotid interventions, Medicare ICD-9 codes for cerebrovascular events, and SEER data for stroke as the cause of death were collected. Similarly, Medicare CPT and ICD-9 codes for peripheral vascular disease (PVD) were assessed to serve as an internal control between treatment groups. Results: A total of 1413 assessable patients (RT, n=1055; surgery, n=358) were analyzed. The actuarial 10-year risk of CVD was 56.5% (95% confidence interval 51.5%-61.5%) for the RT cohort versus 48.7% (41.1%-56.3%) in the surgery cohort (P=.27). The actuarial 10-year risk of PVD did not differ between the RT (52.7% [48.1%-57.3%]) and surgery cohorts (52.6% [45.2%-60.0%]) (P=.89). Univariate analysis showed an increased association of CVD with more recent diagnosis (P=.001) and increasing age (P=.001). On multivariate Cox analysis, increasing age (P<.001) and recent diagnosis (P=.002) remained significantly associated with a higher CVD risk, whereas the association of RT and CVD remained not statistically significant (HR=1.11 [0.91-1.37,] P=.31). Conclusions: Elderly patients with early-stage laryngeal cancer have a high burden of cerebrovascular events after surgical management or RT. RT and surgery are associated with comparable risk for subsequent CVD development after treatment in elderly patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

1 H NMR-based metabolomics of antimalarial plant species traditionally used by Vha-Venda people in Limpopo Province, South Africa and isolation of antiplasmodial compounds

The Vha-Venda people living in rural areas of Limpopo Province of South Africa regularly use traditional plant-based medicines to treat malaria. In our earlier publication, twenty indigenous plant species used to treat malaria or its symptoms by Vha-Venda people were evaluated for antiplasmodial activity. The main objective of the current paper was to assess the robustness of NMR-based metabolomics in discriminating classes of secondary compounds that are responsible for the observed antimalarial activity and the isolation of antiplasmodial compounds. Twenty dichloromethane extracts were reconstituted in CDCl 3 , subjected to 1 H NMR-based metabolomic analysis on a Varian 600 MHz spectrometer and the acquired 1 H NMR spectra were then evaluated collectively using multivariate data analysis (MDA). Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures–Discriminant Analysis (OPLS-DA) were used to ‘globally’ discern antiplasmodial profiles. A contribution plot was then generated from the OPLS-DA scoring plot in an attempt to determine the classes of compounds that are responsible for the observed grouping. Further phytochemical analyses were conducted on the lipophilic extracts of Tabernaemontana elegans and Vangueria infausta subsp. infausta. These best candidates were fractionated, purified and their isolated compounds identified based on conventional chromatographic and spectroscopic techniques. The PCA did not separate the acquired profiles according to the detected antiplasmodial bioactivity. Application of a supervised OPLS-DA on the 1 H NMR profiles resulted in a discrimination pattern that could be correlated to the observed antimalarial bioactivity. A contribution plot generated from the OPLS-DA scoring plot illustrated the classes of compounds responsible for the observed grouping. Prominent peaks were observed in the aromatic, sugar-based/N-containing and aliphatic spectral regions of the contribution plot. Two known indole alkaloids were isolated from T. elegans, and identified as tabernaemontanine (IC 50 = 12.0±0.8 µM) and dregamine (IC 50 = 62.0±2.4 µM). Friedelin (IC 50 = 7.20±0.5 µM) and morindolide (IC 50 = 107.1±0.6 µM) were isolated from V. infausta subsp. infausta. This is the first report of the rare iridoid lactone, morindolide's antimalarial activity. While these two compounds have been previously identified, this is the first account of their occurrence in the genus Vangueria. The study illustrated the potential of NMR-based metabolomics in discriminating classes of compounds that may be attributed to antiplasmodial activity. Finally and additionally, the study demonstrated the potential of discovering novel antiplasmodial scaffolds from medicinal plants and the rationale for the bioprospecting antimalarial plant species used by Vha-Venda people.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Expression and prognostic role of orphan receptor GPR110 in glioma

Glioma is the most common type of malignancy in the central nervous system, which has a poor prognosis due to its rapid progression and diffuse invasion. Identification of novel biomarkers for glioma would be invaluable for studying disease mechanism and improving prognosis. Orphan G protein-coupled receptor 110 (GPR110) belongs to the subfamily VI of adhesion GPCR. The knowledge of the ligand, signaling pathway or physiology function of GPR110 is poorly elucidated. The potential role of GPR110 as an oncogene in mouse has been recently reported by mutagenesis screen. However, its expression and role in human glioma hasn't been identified. Here in the current study, we initially explored the RNA and protein expression of GPR110 in patients with glioma. Statistical analysis proved that GPR110 was highly expressed in some patients, which was correlated with advanced disease stages. Furthermore, univariate and multivariate analyses revealed its role as an independent prognostic biomarker for the overall survival of glioma patients. Interestingly, cellular studies showed that overexpression or knockdown of GPR110 in U87 cells didn't affect cell proliferation and migration. However, the invasion of U87 cells was significantly enhanced by GPR110-overepxression, while inhibited by GPR110-knockdown. The detailed mechanisms remain further investigation although our results suggested the possible participation of STAT3 instead of ERK in the GPR110 signaling pathways. - Highlights: • GPR110 was highly expressed in glioma than normal brain tissues. • High GPR110 indicates poor overall survival of glioma patients. • GPR110 enhance cell invasion without affecting cell proliferation and migration. • GPR110 inhibit the activation of STAT3, but not ERK protein.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Decoding the Mechanisms of Phase Transitions from In Situ Microscopy Observations

Abstract Analysis of the temperature‐ and stimulus‐dependent imaging data toward elucidation of the physical transformations is an ubiquitous problem in multiple fields. Here, temperature‐induced phase transition in BaTiO 3 is explored using the machine learning analysis of domain morphologies visualized via variable‐temperature scanning transmission electron microscopy (STEM) imaging data. This approach is based on the multivariate statistical analysis of the time or temperature dependence of the statistical descriptors of the system, derived in turn from the categorical classification of observed domain structures or projection on the continuous parameter space of the feature extraction‐dimensionality reduction transform. The proposed workflow offers a powerful tool for the exploration of the dynamic data based on the statistics of image representation as a function of the external control variable to visualize the transformation pathways during phase transitions and chemical reactions. This can include the mesoscopic STEM data as demonstrated here, but also optical, chemical imaging, etc., data. It can further be extended to the higher dimensional spaces, for example, analysis of the combinatorial libraries of materials compositions.

Valleti, Sai Mani Prudhvi↗