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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Choice reaction time and grip strength as predictors of cardiovascular mortality in middle‐aged and elderly Japanese: from the Radiation Effects Research Foundation Adult Health study

Abstract Background Cognitive function and physical function are important predictors of mortality. Aim To investigate whether or not reaction time (RT) as a cognitive function and grip strength (GS) as a physical function were associated, alone or in combination, with mortality from heart disease or stroke. Methods The subjects included 4901 Adult Health Study participants in Hiroshima who had undergone RT and GS measurements, were 35–74 years old at baseline (1970–1972) and were followed until the end of 2007. Results After adjustment for other potential risk factors, RT was positively and GS was negatively associated with mortality from both heart disease and stroke. These associations were persistent in the model when adjusting simultaneously for RT, GS and other factors, but hazard ratios were attenuated. When we evaluated the associations by baseline age and gender, we found the greater hazard ratios for RT in the younger cohort, but no clear modification by age for GS. The interaction between RT and GS was statistically significant ( P = 0.012) for stroke mortality. In the stratified analyses divided using the age‐specific median value of RT or GS, the estimated hazard ratio of stroke mortality for RT was significant in participants with weak or strong GS but greater in the former, and for GS, it was only significant in participants with slow RT. Conclusion RT and GS, alone and in combination, predicted heart disease and stroke mortalities. Interventions for both cognitive function and physical function may be beneficial for the prevention of cardiovascular disease mortality.

Shimizu, Masaki↗
NASA NTRS2003

Nonlinear Gulf Stream Interaction with the Deep Western Boundary Current System: Observations and a Numerical Simulation

Gulf Stream (GS) separation near its observed Cape Hatteras (CH) separation location, and its ensuing path and dynamics, is a challenging ocean modeling problem. If a model GS separates much farther north than CH, then northward GS meanders, which pinch off warm core eddies (rings), are not possible or are strongly constrained by the Grand Banks shelfbreak. Cold core rings pinch off the southward GS meanders. The rings are often re-absorbed by the GS. The important warm core rings enhance heat exchange and, especially, affect the northern GS branch after GS bifurcation near the New England Seamount Chain. This northern branch gains heat by contact with the southern branch water upstream of bifurcation, and warms the Arctic Ocean and northern seas, thus playing a major role in ice dynamics, thermohaline circulation and possible global climate warming. These rings transport heat northward between the separated GS and shelf slope/Deep Western Boundary Current system (DWBC). This region has nearly level time mean isopycnals. The eddy heat transport convergence/divergence enhances the shelfbreak and GS front intensities and thus also increases watermass transformation. The fronts are maintained by warm advection by the Florida Current and cool advection by the DWBC. Thus, the GS interaction with the DWBC through the intermediate eddy field is climatologically important.

Dietrich, David E.↗
DOE OSTI2017

An Electrospray Ionization Mass Spectrometry Study on the “In Vacuo” Hetero-Oligomers Formed by the Antimicrobial Peptides, Surfactin and Gramicidin S

It was previously observed that the lipopeptide surfactants in surfactin (Srf) have an antagonistic action towards the highly potent antimicrobial cyclodecapeptide, gramicidin S (GS). This study reports on some of the molecular aspects of the antagonism as investigated through complementary electrospray ionization mass spectrometry techniques. We were able to detect stable 1:1 and 2:1 hetero-oligomers in a mixture of surfactin and gramicidin S. The noncovalent interaction between GS and Srf, with the proposed equilibrium: GS~Srf↔GS+Srf correlated to apparent K{sub d} values of 6–9 μM in gas-phase and 1 μM in aqueous solution. The apparent K{sub d} values decreased with a longer incubation time and indicated a slow oligomerization equilibrium. Furthermore, the low μM K{sub d}{sup app} values of GS~Srf↔GS+Srf fell within the biological concentration range and related to the 2- to 3-fold increase in [GS] needed for bacterial growth inhibition in the presence of Srf. Competition studies indicated that neither Na{sup +} nor Ca{sup 2+} had a major effect on the stability of preformed heterodimers and that GS in fact out-competed Ca{sup 2+} and Na{sup +} from Srf. Traveling wave ion mobility mass spectrometry revealed near symmetrical peaks of the heterodimers correlating to a compact dimer conformation that depend on specific interactions. Collision-induced dissociation studies indicated that the peptide interaction is most probably between one Orn residue in GS and the Asp residue, but not the Glu residue in Srf. We propose that flanking hydrophobic residues in both peptides stabilize the antagonistic and inactive peptide hetero-oligomers and shield the specific polar interactions in an aqueous environment. .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The response of stomatal conductance to seasonal drought in tropical forests

Stomata regulate CO2 uptake for photosynthesis and water loss through transpiration. The approaches used to represent stomatal conductance (gs) in models vary. In particular, current understanding of drivers of the variation in a key parameter in those models, the slope parameter (i.e. a measure of intrinsic plant water-use-efficiency), is still limited, particularly in the tropics. Here we collected diurnal measurements of leaf gas exchange and water potential (?leaf), and a suite of plant traits from the upper canopy of 15 tropical trees in two contrasting Panamanian forests throughout the dry season of the 2016 El Niño. The plant traits included wood density, leaf-mass-per-area (LMA), leaf carboxylation capacity (Vc,max25), leaf water content, the degree of isohydry, and predawn ?leaf. We first investigated how the choice of four commonly used leaf-level gs models with and without the inclusion of ?leaf as an additional predictor variable influence the ability to predict gs, and then explored the abiotic (i.e. month, site-month interaction) and biotic (i.e. tree-species-specific characteristics) drivers of slope parameter variation. Our results show that the inclusion of ?leaf did not improve model performance and that the models that represent the response of gs to vapor pressure deficit performed better than corresponding models that respond to relative humidity. Within each gs model, we found large variation in the slope parameter, and this variation was attributable to the biotic driver, rather than abiotic drivers. We further investigated potential relationships between the slope parameter and the six available plant traits mentioned above, and found that only one trait, LMA, had a significant correlation with the slope parameter (R2=0.66, n=15), highlighting a potential path towards improved model parameterization. This study advances understanding of gs dynamics over seasonal drought, and identifies a practical, trait-based approach to improve modeling of carbon and water exchange in tropical forests.

carbon and water exchange, stomatal conductance mo↗
DOE OSTI2022

Process-based modeling of soil nitrous oxide emissions from United States corn fields under different management and climate scenarios coupled with evaluation using regional estimates

Direct emissions of soil nitrous oxide during a growing season (N 2 O gs ) can be quantified with process-based models considering interactions between management, climate, and soil moisture when key data are available. We used an adapted “parameterized CENTURY/DAYCENT-model” ( p CENTURY) calibrated with crop growth and soil organic matter decay coefficients at the county-level for the estimation of N 2 O gs in the United States Corn Belt. Model estimated N 2 O-emissions from corn-based biofuels scenarios considering crop rotation, fertilizer inputs, tillage, and weather were compared against meta-summary of field observations from 55 studies. Both model and meta-summary ranked N 2 O gs -emissions to be corn > wheat > soybean phase while model likely underestimated cover crop N 2 O gs -emissions. The N 2 O gs -emissions and the associated emission factors (EFs) were modeled and summarized to be greater after anhydrous ammonia than urea application and from conventional tilled than non-tilled fields. Modeled and observed N 2 O gs -emissions after organic and inorganic fertilizer amendment did not differ due to high variability associated with the treatments. However, the organic fertilizer associated EFs were greater according to meta-summary data because of N input rates. Regionalized weather scenarios indicate hotspots for N 2 O gs -emissions can occur where crop N uptake is limited during dry years and in eastern states also during normal or wet seasons. The p CENTURY-derived N 2 O gs EFs (0.91 ± 0.19%) for counties investigated were only slightly lower than literature (1.07 ± 0.57%) or Tier-1 (1%) values. Our preliminary evaluation of regional soil moisture estimates showed reasonable agreement between monthly soil moisture estimates and the North American Soil Moisture Dataset during the growing season, but overestimation of soil moisture in winter-spring can influence the estimates of annual N 2 O emissions so future work is needed to calibrate soil moisture-associated model parameters. Our work provided scenario-based estimates of climate and management impacts on soil N 2 O gs -emissions together with valuable spatial insights into EFs that will be improved by more accurate information of fertilizer inputs and more temporally refined model evaluation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign and the 1998 First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). We investigate two related approaches to prediction of GS cloud properties from SGS variability: the critical saturation ratio method, and the critical relative humidity method. We find significant correlation between GS cloud water and SGS supersaturation when the critical saturation ratio is set at 100%, as well as a notable relationship between GS cloud water and the width of the SGS total water distribution. Critical relative humidity also compares well with GS cloud water. However, we also find that the assumptions of a static critical saturation ratio of 100% to be unrealistic, as well as a fixed SGS distribution width. Empirical calculations from the ARISE data show a large sensitivity of these SGS variables to GS relative humidity, and so a SGS parameterization allowing them to vary according to GS thermodynamic properties may result in more realistic GS cloud water values.

J. Brant Dodson↗
DOE OSTI2025

Topological and magnetic properties of a noncollinear spin state on a honeycomb lattice in a magnetic field

Here, this paper studies the topological and magnetic properties of a noncollinear spin state on a honeycomb lattice that evolves from coplanar to ferromagnetic with a magnetic field applied along the z axis. The coplanar state is stabilized by nearest-neighbor ferromagnetic interactions, single-ion anisotropy along z, and DzyaloshinskiiMoriya interactions between next-nearest-neighbor sites. Below the critical field H$_c$ that aligns the spins, the magnetic unit cell contains six sites and the spin dynamics contains six magnon modes. Although the classical energy is degenerate with respect to the twist angle φ between nearest-neighbor spins, the dependence of the free energy on φ at low temperatures is dominated by the magnon zero-point energy, which contains extremum at φ = πl/3 for integer l. The only unique ground states GS(φ) have l = 0 or 1. For H < H$'_c$, the zero-point energy has minima at even l and the ground state is GS(0); for H$'_c$ < H < H$'_c$, the zero-point energy has minima at odd l and the ground state is GS(π/3). In GS(0), the magnon density of states exhibits five distinct topological phases with increasing field associated with the opening and closing of energy gaps between two or three magnonic bands. While the Berry curvature vanishes for the coplanar φ = 0 phase in zero field, the Berry curvature and Chern numbers exhibit signatures of the five topological phases below H$'_c$. Whereas the Berry curvature and Chern number are sensitive to changes in the magnon density of states within GS(π/3), the inelastic spectrum S(k,ω) is sensitive to changes in the intensity of the magnon modes in the different magnetic phases GS(0) and GS(π/3) rather than the five topological phases within GS(π/3).

Fishman, Randy S. [Oak Ridge National Laboratory (↗
NASA NTRS2014

Analysis and Prediction of Weather Impacted Ground Stop Operations

When the air traffic demand is expected to exceed the available airport's capacity for a short period of time, Ground Stop (GS) operations are implemented by Federal Aviation Administration (FAA) Traffic Flow Management (TFM). The GS requires departing aircraft meeting specific criteria to remain on the ground to achieve reduced demands at the constrained destination airport until the end of the GS. This paper provides a high-level overview of the statistical distributions as well as causal factors for the GSs at the major airports in the United States. The GS's character, the weather impact on GSs, GS variations with delays, and the interaction between GSs and Ground Delay Programs (GDPs) at Newark Liberty International Airport (EWR) are investigated. The machine learning methods are used to generate classification models that map the historical airport weather forecast, schedule traffic, and other airport conditions to implemented GS/GDP operations and the models are evaluated using the cross-validations. This modeling approach produced promising results as it yielded an 85% overall classification accuracy to distinguish the implemented GS days from the normal days without GS and GDP operations and a 71% accuracy to differentiate the GS and GDP implemented days from the GDP only days.

Analysis↗
DOE OSTI2016

Predicting the 5-Year Risk of Biochemical Relapse After Postprostatectomy Radiation Therapy in ≥PT2, pN0 Patients With a Comprehensive Tumor Control Probability Model

Purpose: To fit the individual biochemical recurrence-free survival (bRFS) data from patients treated with postprostatectomy radiation therapy (RT) with a comprehensive tumor control probability (TCP) model. Methods and Materials: Considering pre-RT prostate-specific antigen (PSA) as a surrogate of the number of clonogens, bRFS may be expressed as a function of dose-per-fraction–dependent radiosensitivity (α{sub eff}), the number of clonogens for pre-RT PSA = 1 ng/mL (C), and the fraction of patients who relapse because of clonogens outside the treated volume (K), assumed to depend (linearly or exponentially) on pre-RT PSA and Gleason score (GS). Data from 894 node-negative, ≥pT2, pN0 hormone-naive patients treated with adjuvant (n=331) or salvage (n=563) intent were available: 5-year bRFS data were fitted grouping patients according to GS (<7:392, =7:383, >7:119). Results: The median follow-up time, pre-RT PSA, and dose were 72 months, 0.25 ng/mL, and 66.6 Gy (range 59.4-77.4 Gy), respectively. The best-fit values were 0.23 to 0.26 Gy{sup −1} and 10{sup 7} for α{sub eff} and C for the model considering a linear dependence between K and PSA. Calibration plots showed good agreement between expected and observed incidences (slope: 0.90-0.93) and moderately high discriminative power (area under the curve [AUC]: 0.68-0.69). Cross-validation showed satisfactory results (average AUCs in the training/validation groups: 0.66-0.70). The resulting dose-effect curves strongly depend on pre-RT PSA and GS. bRFS rapidly decreases with PSA: the maximum obtainable bRFS (defined as 95% of the maximum) declined by about 2.7% and 4.5% for each increment of 0.1 ng/mL for GS <7 and ≥7, respectively. Conclusions: Individual data were fitted by a TCP model, and the resulting best-fit parameters were radiobiologically consistent. The model suggests that relapses frequently result from clonogens outside the irradiated volume, supporting the choice of lymph-node irradiation, systemic therapy, or both for specific subgroups (GS <7: PSA >0.8-1.0 ng/mL; GS ≥7: PSA >0.3 ng/mL). Early RT should be preferred over delayed RT; the detrimental effect of PSA increase can never be fully compensated by increasing the dose, especially for patients with GS ≥7.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Mechanism of endosomal escape by p H -responsive nucleic-acid vectors

Successful intracellular delivery of nucleic acids (NAs) hinges on many factors, one of them being NAs’ efficacious escape from endosomes. As competent NA vectors, pH-responsive gemini surfactants (GSs) might achieve high efficacy by facilitating endosomal escape. However, how the GSs assist the escape remains debated as many proposed mechanisms still lack experimental support, which hinders replication and further improvement of the efficient delivery. Here, via UV, fluorescence spectroscopy, and small-angle neutron scattering (SANS), we examined a pH-responsive GS's and a pH-unresponsive GS's capabilities to compact DNA and withstand binding competition, and their interactions with model endosomal and lysosomal membranes, at varied pHs. Acidification-driven enhancement of DNA-compaction capability and of stability against binding competition were found specific to the pH-responsive GS. Alongside the pH-responsive GS's structural perturbation to the membranes as observed with SANS, the features suggest that pH-responsive GSs facilitate endosomal escape by releasing excess GS molecules from DNA-GS complexes upon acidification in endosome maturation, with the released GS molecules disrupting endosomal and lysosomal membranes and thereby assisting the escape. Here a general design principle for NA vectors is proposed on the basis of this experimental finding.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch-screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass-forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, in this work, we explore the application of an open-source pre-trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics-informed machine learning (PIML)-predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top-performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). Multiple models/reanalyses use SGS supersaturated total water (relative to GS saturation) as a threshold for partitioning available water for condensation, and indeed we find significant correlation between GS cloud water and SGS supersaturation. However, we also find that the assumption of a static threshold of 100% saturation to be unrealistic. Empirical calculations from the ARISE data show a large sensitivity of this threshold to GS relative humidity, and so a microphysical parameterization allowing the threshold to vary according to GS thermodynamic properties may result in more realistic GS cloud water values. Finally, to determine how sensitive the ARISE-derived results are to that particular campaign, we include additional data from the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) conducted in 1998. The inclusion of the second dataset will help with demonstrating the robustness of the results and their utility in improving the representation of Arctic clouds in models and reanalyses.

J Brant Dodson↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign and the 1998 First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). We examine the influence of three assumed SGS parameters on the estimation of GS cloud water: the width of the SGS PDF of total water (ΔQT), the shape of the SGS PDF, and the critical saturation ratio (Scrit), which partitions the SGS PDF into water that is available or not for conversion to cloud water. Both Scrit and ΔQT influence predicted GS cloud water strongly. ARISE and FIRE-ACE disagree somewhat in the details, but both campaigns support the possibility that more realistic representations of these two parameters may lead to more realistic GS cloud water. In particular, both parameters are sensitive to GS relative humidity, and so we examine the effects of allowing these quantities to vary as an empirically-derived linear function of GS relative humidity. In contrast, the shape of the PDF has little effect on the predicted cloud water – a surprising result that merits additional investigation.

J Brant Dodson↗
DOE OSTI2017

Changes in global vegetation activity and its driving factors during 1982–2013

Vegetation activity plays a crucial role in the global carbon cycle and climate. Many studies have examined recent changes in vegetation growth and the associated local climatic drivers. They revealed a global greening trend during the recent decades. However, few studies have analyzed how remote oceanic conditions affect land vegetation growth through atmospheric teleconnection, and the causes of the recent greening needs further investigation. Here in this study, we investigate the spatio-temporal variations (including trends) of vegetation activity using satellite data of growing-season normalized difference vegetation index (NDVI gs ), and examine their relationship to local and remote climate oscillations and external anthropogenic forcing by statistical means. As expected, there is an increasing trend in global-mean NDVI gs from 1982–2013, with significant greening over Europe and many other land areas. NDVI gs is temperature-limited at northern high-latitudes, but water-limited in arid and semi-arid regions, and radiation-limited in the Amazon and eastern and southern Asia. Globally, El Niño-Southern Oscillation (ENSO) is the leading climatic driver of interannual variability of NDVI gs , especially over southern and eastern Africa, eastern Australia, northeastern Asia, and northern South America. Consistent with previous modeling studies, a regression-based attribution analysis suggests that historical anthropogenic forcing (mainly increases in greenhouse gases) explains about two thirds of the NDVI gs trend from 1982 to 2013, with the rest coming mainly from the Atlantic Multi-decadal Oscillation (AMO). Contributions to the recent NDVI gs trend from ENSO and Pacific decadal variability and Artctic Oscillation appear to be small.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Effects of PQ's cytotoxicity on secretory vesicles in astroglia: Expression alternation of secretogranin II and its potential interaction with intracellular factors

Highlights: • PQ upregulated SCG2 expression and altered its subcellular location in astroglia. • SCG2 knockdown dysregulated GS and IL-6 expressions on RNA and protein levels. • SCG2-positive LDCVs were partially involved in trafficking of IL-6 but not GS. • SCG2 may contribute to PQ toxicology by regulating neurotransmitters and cytokines. It has been extensively characterized that paraquat (PQ) selectively targets to the substantia nigra and exerts neurotoxic actions on dopaminergic neurons. However, a little knowledge is available about astroglia in PQ exposure, especially its complex secretory machinery. To explore this point, we built up a PQ-induced model in cultural U118 astrocyte. Since the granin family is considered as a master regulator of cargo sorting and large dense core vesicles (LDCVs) biogenesis in the regulated secretory pathway of nervous and neuroendocrine cells, the current study focused on one member, secretogranin II (SCG2) and investigated its alternation and potential relationship with other astrocyte-derived factors under PQ insult. We found that PQ upregulated SCG2 expression on both RNA and protein levels and stimulated the mRNA expression of neurotrophic factors, cytokines and glutamine synthetase (GS) simultaneously. RNAi knockdown of SCG2 did not rescue the cell cycle arrest induced by PQ but affected expressions of IL-6 and GS on mRNA and protein levels. Further studies on subcellular location showed that SCG2-positive secretory granules were partially colocalized with IL-6 but not GS in PQ exposure astrocyte. Taken together, our findings indicate that the expression alternation of SCG2 under astroglial activation by PQ may be necessary compensation for cargo sorting and LDCV biogenesis. The involvement of the IL-6 and GS suggests that the SCG2 may potentially regulate inflammatory factors and excitatory neurotransmitter to the cytotoxicity of PQ on astroglia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Toward Prostate Cancer Contouring Guidelines on Magnetic Resonance Imaging: Dominant Lesion Gross and Clinical Target Volume Coverage Via Accurate Histology Fusion

Purpose: Defining prostate cancer (PCa) lesion clinical target volumes (CTVs) for multiparametric magnetic resonance imaging (mpMRI) could support focal boosting or treatment to improve outcomes or lower morbidity, necessitating appropriate CTV margins for mpMRI-defined gross tumor volumes (GTVs). This study aimed to identify CTV margins yielding 95% coverage of PCa tumors for prospective cases with high likelihood. Methods and Materials: Twenty-five men with biopsy-confirmed clinical stage T1 or T2 PCa underwent pre-prostatectomy mpMRI, yielding T2-weighted, dynamic contrast-enhanced, and apparent diffusion coefficient images. Digitized whole-mount histology was contoured and registered to mpMRI scans (error ≤2 mm). Four observers contoured lesion GTVs on each mpMRI scan. CTVs were defined by isotropic and anisotropic expansion from these GTVs and from multiparametric (unioned) GTVs from 2 to 3 scans. Histologic coverage (proportions of tumor area on co-registered histology inside the CTV, measured for Gleason scores [GSs] ≥6 and ≥7) and prostate sparing (proportions of prostate volume outside the CTV) were measured. Nonparametric histologic-coverage prediction intervals defined minimal margins yielding 95% coverage for prospective cases with 78% to 92% likelihood. Results: On analysis of 72 true-positive tumor detections, 95% coverage margins were 9 to 11 mm (GS ≥ 6) and 8 to 10 mm (GS ≥ 7) for single-sequence GTVs and were 8 mm (GS ≥ 6) and 6 mm (GS ≥ 7) for 3-sequence GTVs, yielding CTVs that spared 47% to 81% of prostate tissue for the majority of tumors. Inclusion of T2-weighted contours increased sparing for multiparametric CTVs with 95% coverage margins for GS ≥6, and inclusion of dynamic contrast-enhanced contours increased sparing for GS ≥7. Anisotropic 95% coverage margins increased the sparing proportions to 71% to 86%. Conclusions: Multiparametric magnetic resonance imaging–defined GTVs expanded by appropriate margins may support focal boosting or treatment of PCa; however, these margins, accounting for interobserver and intertumoral variability, may preclude highly conformal CTVs. Multiparametric GTVs and anisotropic margins may reduce the required margins and improve prostate sparing.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Benchmarking Guanidinium Organosulfonate Hydrogen-Bonded Frameworks for Structure Determination of Encapsulated Guests

Single crystal X-ray diffraction (SCXRD) is arguably the most definitive method for molecular structure determination, but it is often challenged by compounds that are liquids or oils at room temperature or do not form crystals adequate for analysis. Our laboratory previously reported a simple, cost-effective, single-step crystallization method based on guanidinium organosulfonate (GS) hydrogen bonded frameworks for structure determination of a wide range of encapsulated guest molecules, including assignment of the absolute configuration of chiral centers. Herein, we expand on those results and report a head-to-head comparison of the GS method with adamantoid “molecular chaperones”, which have been reported to be useful hosts for structure determination. Inclusion compounds limited to only two GS hosts are characterized by low R1 values and Flack parameters, infrequent disorder of the host and guest, and manageable disorder when it does exist. The structures of some target molecules that were not included or resolved using the adamantoid chaperones were successfully included and resolved by the GS hosts, and vice versa. Of the 32 guests attempted by the GS method, 31 inclusion compounds afforded successful guest structure solutions, a 97% success rate. The GS hosts and adamantoid chaperones are complementary with respect to guest inclusion, arguing that both should be employed in the arsenal of methods for structure determination. Furthermore, the low cost of organosulfonate host components promises an accessible route to molecular structure determination for a wide range of users.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Quasi-Periodic Oscillations in Black Hole Candidates as an Indicator of Transition Between Low and High States

By comparing positions on a spectral color-color diagram from 10 black hole candidates (BHCS) observed with Ginga (1354-64, 1826-24, 1630-47, LMC X-1, LMC X-3, GS 2000+25, GS 2023+33, GS 1124-68, Cyg X-1, and GX 339-4) with the observed broad-band noise (0.001- 64 Hz; BBN) and quasi-periodic oscillation (QPO) variability, we find that the so-called "Very High State" is spectrally intermediate to the Soft/High-State and Hard/Low-State. We find a transition point in spectral hardness where the dependence of the BHC QPO centroid frequency (of GS 1124-68 and GX 339-4) on spectral hardness switches from a correlation to an anti-correlation; where the BBN variability switches from High-State to Low-State; and where the spectral hardness of the QPO relative to that of the BBN variability is a maximum. This coincidence of changing behavior in both the QPO and the broad-band variability leads us to hypothesize that the QPO is due to interaction between the physical components which dominate the behaviors of BHCs when they occupy the Hard/Low and Soft/High States. We conclude that these QPO should be observed from BHCs during transition between these two states. Comparison with QPO and BBN behavior observed during the 1996 transition of Cyg X-1 supports this hypothesis. We also report 1-3 Hz QPO observed in GS 2000+25 and Cyg X-1 in the Hard/Low State, and we compare these to the QPO observed in GS 1124-68 and GX 339-4.

Rutledge, Robert E↗