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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Preliminary verification of the MCNP perturbation and fixed-source tally sensitivity tools

Integral benchmark experiments are vital in the adjustment and validation of the nuclear data that govern predictive simulations across the nuclear community. The nuclear data sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®) transport code are currently limited; however, expanding sensitivity capabilities will allow benchmark experiments to be designed to resolve compensating errors and adjust nuclear data where previously prohibitively difficult. This paper provides details of a preliminary verification for the use of (i.) the recently revised perturbation and (ii.) developmental fixed-source sensitivity tools within MCNP to calculate sensitivities of tallied responses (such as current integrated over a surface, F1, and flux averaged over a cell, F4) to nuclear data in fixed-source simulations. Energy-binned and energy-integrated sensitivities calculated with these tools are compared against sensitivities calculated using a central-difference approximation. Here, the verification is completed for four configurations of a benchmarked system using a 4.5-kg plutonium sphere surrounded by varying amounts of copper and/or polyethylene. The results show that sensitivities calculated with the perturbation and fixed-source sensitivity tools agree with the central-difference-based approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

The transcription factor Prep1 controls hepatic insulin sensitivity and gluconeogenesis by targeting nuclear localization of FOXO1

Liver plays a key role in controlling body carbohydrate homeostasis by switching between accumulation and production of glucose and this way maintaining constant level of glucose in blood. Increased blood glucose level triggers release of insulin from pancreatic β-cells. Insulin represses hepatic glucose production and increases glucose accumulation. Insulin resistance is the main cause of type 2 diabetes and hyperglycemia. Currently thiazolidinediones (TZDs) targeting transcriptional factor PPARγ are used as insulin sensitizers for treating patients with type 2 diabetes. However, TZDs are reported to be associated with cardiovascular and liver problems and stimulate obesity. Thus, it is necessary to search new approaches to improve insulin sensitivity. A promising candidate is transcriptional factor Prep1, as it was shown earlier it could affect insulin sensitivity in variety of insulin-sensitive tissues. The aim of the present study was to evaluate a possible involvement of transcriptional factor Prep1 in control of hepatic glucose accumulation and production. We created mice with liver-specific Prep1 knockout and discovered that hepatocytes derived from these mice are much more sensitive to insulin, comparing to their WT littermates. Incubation of these cells with 100 nM insulin results in almost complete inhibition of gluconeogenesis, while in WT cells this repression is only partial. However, Prep1 doesn't affect gluconeogenesis in the absence of insulin. Also, we observed that nuclear content of gluconeogenic transcription factor FOXO1 was greatly reduced in Prep1 knockout hepatocytes. These findings suggest that Prep1 may control hepatic insulin sensitivity by targeting FOXO1 nuclear stability. - Highlights: • A novel model of liver-specific Prep1 knockout is established. • Ablation of Prep1 in hepatocytes increases insulin sensitivity. • Prep1 controls hepatic insulin sensitivity by regulating localization of FOXO1. • Prep1 regulates localization of FOXO1 via Wnt/β-catenin signaling pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Dual regulation of skin sensitizer-induced HMOX1 expression by Bach1 and Nrf2: Comparison to regulation of the AKR1C2-ARE element in the KeratinoSens cell line

Heme oxygenase (decycling) 1 (HMOX1) is the most consistently found genetic marker induced by skin sensitizers. HMOX1 is often referred to as typical gene regulated by nuclear factor erythroid 2-related factor 2 (Nrf2), however, it is also regulated by other DNA-binding factors, including BTB and CNC homolog 1 (Bach1). The KeratinoSens™ assay is the first validated in vitro assay for sensitizers that measures gene induction. It is based on luciferase expression regulated by the antioxidant response element (ARE) of the aldoketoreductase 1C2 (AKR1C2) gene. Luciferase upregulation is dependent on Nrf2, while HMOX1 upregulation is only partially Nrf2-dependent. Thus, sensitizer-dependent activation of HMOX1 may integrate multiple signals thereby providing additional information. We constructed reporter cell lines containing the full HMOX1 regulatory region or the HMOX1-ARE sequence and compared them with the construct containing the AKR1C2-ARE sequence. Induction of the AKR1C2-ARE depends on Nrf2, but not on the repressor Bach1. Results obtained with HMOX1-ARE and the full HMOX1 promoter indicate that, within the HMOX1 promoter, the HMOX1-ARE is sufficient to explain the induction by sensitizers and that (i) inhibiting Bach1 leads to strong basal expression, (ii) fold-induction by sensitizers above this level is reduced in the absence of Bach1 and (iii) these constructs are less dependent on Nrf2 as compared to the AKR1C2-ARE. Nevertheless, congruent dose response curves for luciferase activity were obtained with all constructs. Thus, while sensitizer-induced HMOX1 activation is dependent on Nrf2 and Bach1, all constructs give identical information for the in vitro prediction of the sensitization potential. - Highlights: • HMOX1 is a key genetic marker up-regulated by skin sensitizers. • HMOX1-, but not AKR1C2-upregulation, is dependent on both Nrf2 and Bach1. • AKR1C2 and HMOX1-dependent reporter constructs yield congruent dose response curves. • Combining both constructs offers no advantage over either construct used alone.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Low temperature annealed amorphous indium gallium zinc oxide (a-IGZO) as a pH sensitive layer for applications in field effect based sensors

The use of a-IGZO instead of the conventional high-k dielectrics as a pH sensitive layer could lead to the simplification of fabrication steps of field effect based devices. In this work, the pH sensitivities of a-IGZO films directly deposited over a SiO{sub 2}/Si surface were studied utilizing electrolyte-insulator-semiconductor (EIS) structures. Annealing of the films was found to affect the sensitivity of the devices and the device with the film annealed at 400 {sup o}C in N{sub 2} ambience showed the better sensitivity, which reduced with further increase in the annealing temperature to 500 {sup o}C. The increased pH sensitivity with the film annealed at 400 {sup o}C in N{sub 2} gas was attributed to the enhanced lattice oxygen ions (based on the XPS data) and improved C-V characteristics, while the decrease in sensitivity at an increased annealing temperature of 500 {sup o}C was attributed to defects in the films as well as the induced traps at the IGZO/SiO{sub 2} interface based on the stretched accumulation and the peak in the inversion region of C-V curves. This study could help to develop a sensor where the material (a-IGZO here) used as the active layer in a thin film transistors (TFTs) possibly could also be used as the pH sensitive layer without affecting the TFT characteristics, and thus obviating the need of high-K dielectrics for sensitivity enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Sensitivity of magnetic islands in permanent magnet stellarators using the gradient and Hessian methods

Stellarator plasmas are known to be very sensitive to perturbations in the magnetic field. The permanent magnet stellarator was in part developed as a solution to high machining tolerances placed on the shape properties of electromagnetic coils in traditional stellarators. However, as a consequence of this high sensitivity to the field structure, sensitivities of permanent magnet stellarator plasmas to perturbations of permanent magnet properties must necessarily be well-understood. The gradient and Hessian matrix methods have been previously demonstrated to be useful sensitivity analysis methods for modular coils. We apply these two methods to the study of island width sensitivities in both the MUSE and PM4STELL permanent magnet stellarator projects. These sensitivity methods were used to determine the relative impacts of permanent magnet parameter perturbations on island widths in the vacuum field approximation of both stellarator equilibria. The square of resonant magnetic field perturbation is used here as a proxy for island width. In particular, gradients of magnetizations of individual magnets were examined in MUSE, as well as gradients of magnet group displacements informed by device design. Three different forms of permanent magnet magnetization perturbations are investigated for MUSE, and the flux surface response to perturbations is demonstrated. The Hessian matrix method is applied to PM4STELL, illustrating the sensitivity of dominant island widths to displacements of toroidal wedge structures. These methods allow for selective direction of experimental resources toward regions of heightened sensitivity, while constraints on less impactful permanent magnet parameters can be relaxed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

SU-E-J-245: Sensitivity of FDG PET Feature Analysis in Multi-Plane Vs. Single-Plane Extraction

Purpose: Sensitivity of PET-derived texture features to reconstruction methods has been reported for features extracted from axial planes; however, studies often utilize three dimensional techniques. This work aims to quantify the impact of multi-plane (3D) vs. single-plane (2D) feature extraction on radiomics-based analysis, including sensitivity to reconstruction parameters and potential loss of spatial information. Methods: Twenty-three patients with solid tumors underwent [{sup 18}F]FDG PET/CT scans under identical protocols. PET data were reconstructed using five sets of reconstruction parameters. Tumors were segmented using an automatic, in-house algorithm robust to reconstruction variations. 50 texture features were extracted using two Methods: 2D patches along axial planes and 3D patches. For each method, sensitivity of features to reconstruction parameters was calculated as percent difference relative to the average value across reconstructions. Correlations between feature values were compared when using 2D and 3D extraction. Results: 21/50 features showed significantly different sensitivity to reconstruction parameters when extracted in 2D vs 3D (wilcoxon α<0.05), assessed by overall range of variation, Rangevar(%). Eleven showed greater sensitivity to reconstruction in 2D extraction, primarily first-order and co-occurrence features (average Rangevar increase 83%). The remaining ten showed higher variation in 3D extraction (average Range{sub var}increase 27%), mainly co-occurence and greylevel run-length features. Correlation of feature value extracted in 2D and feature value extracted in 3D was poor (R<0.5) in 12/50 features, including eight co-occurrence features. Feature-to-feature correlations in 2D were marginally higher than 3D, ∣R∣>0.8 in 16% and 13% of all feature combinations, respectively. Larger sensitivity to reconstruction parameters were seen for inter-feature correlation in 2D(σ=6%) than 3D (σ<1%) extraction. Conclusion: Sensitivity and correlation of various texture features were shown to significantly differ between 2D and 3D extraction. Additionally, inter-feature correlations were more sensitive to reconstruction variation using single-plane extraction. This work highlights a need for standardized feature extraction/selection techniques in radiomics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Impact of Increased Latent Generations on Sensitivity Calculations with SCALE

Analyses of cross section sensitivity data from systems with fissile material allow analysts to associate an importance for each material, nuclide, reaction, and neutron energy by simulating real world criticality scenarios. Although criticality safety validation efforts can be guided by the cross-section sensitivity and uncertainty data generated for a particular system, these calculations can often be computationally expensive and sometimes cumbersome without proper guidance. The TSUNAMI suite within the SCALE code package has several methods for generating sensitivity data, including multigroup and continuous energy (CE) capabilities. The release of SCALE 6.3 has three different CE methods for generating cross section sensitivity data: (1) the Iterated Fission Probability (IFP) method with the KENO Monte Carlo transport solver, (2) the IFP method with the Shift Monte Carlo transport solver, and (3) the Contributon-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method with the KENO Monte Carlo transport solver. Although the CLUTCH method has additional parameters for generating sensitivity data files relative to the IFP method, all three methods use latent generations, which are the generations between an event (i.e., fission) and the assessment of importance based on the asymptotic population of progeny neutrons. Increasing the number of latent generations in a calculation leads to increased discrimination of the sensitivity coefficients but at the cost of the increased uncertainty associated with those generated values. Analysts must balance the accuracy of the sensitivity calculations and its uncertainty with the associated computational cost involved in generating the values. This paper discusses the impact of adjusting the latent generation parameter for a range of sensitivity values and how these changes compare with the direct perturbation values obtained from a change of ±0.5% Δ k in both benchmark and safety application models. Two benchmarks from the International Handbook of Evaluated Criticality Safety Benchmark Experiments and the MPC-32 dual purpose canister for spent nuclear fuel are used for analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Field Sensitivity Analysis of Turbulence Model Parameters for Flow Over a Wing

Reynolds-averaged-Navier-Stokes (RANS) turbulence models are a critical tool in computational-fluid-dynamics simulations of aerodynamic systems, but simulation results can be highly sensitive to RANS-model parameter choices. Sensitivity analysis can be used to quantify these impacts, and the objective of this study is to demonstrate field sensitivity analysis with respect to ten parameters in the 2003 Menter shear-stress-transport (SST) turbulence model. Here, the analysis is demonstrated for an application relevant to wind energy, namely, flow over a NACA 0015 wing at 12 degree angle of attack and a Reynolds number of 1.5 x 10 6 . We quantify sensitivity using Sobol indices and the mean-squared gradient, which are estimated using polynomial chaos and active subspace models, respectively. Our results indicate that there are substantial spatial variations in parameter sensitivities, with different sets of most-sensitive parameters near the wing, as well as in the downstream wake, consistent with the physical interpretations of the turbulence model inputs. We show that, for this particular turbulence model and flow, simultaneous dimension reduction is possible across all quantities of interest, enabling efficient exploration of model outcomes. Ultimately, this analysis provides new insights into turbulence model parameter sensitivities in incompressible flows, and also demonstrates the implementation of field sensitivity analysis for applications relevant to aerodynamics simulations.

17 WIND ENERGY↗
NASA NTRS2013

Climate Sensitivity, Sea Level, and Atmospheric Carbon Dioxide

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3+/-1deg C for a 4 W/sq m CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4deg C for a 4 W/sq m CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.

sea level↗
NASA NTRS2015

Ringberg15: Earth's Climate Sensitivities

To assess gaps in understanding of Earth's climate sensitivities a workshop was organised under the auspices of the WCRP (World Climate Research Programme) Grand Science Challenge on Clouds, Circulation and Climate Sensitivity (Ringberg15). The workshop took place in March 2015 and gathered together over thirty experts from around the world for one week. Attendees each gave short presentations and participated in moderated discussions of specific questions related to understanding Earth's climate sensitivities. Most of the time was focused on understanding of the equilibrium climate sensitivity, defined as the equilibrium near-surface warming associated with a doubling of atmospheric carbon dioxide. The workshop produced nine recommendations, many of them focusing on specific research avenues that could be exploited to advance understanding of climate sensitivity. Many of these dealt, in one fashion or another, with the need to more sharply focus research on identifying and testing story lines for a high (larger than 4 degrees Kelvin) or low (less than 2 degrees Kelvin) equilibrium climate sensitivity. Additionally, a subset of model intercomparison projects (CFMIP (Cloud Feedback Model Intercomparison Project), PMIP (Palaeoclimate Modelling Intercomparison Project), PDRMIP (Precipitation Driver and Response Model Intercomparison Project), RFMIP (Radiative Forcing Model Intercomparison Project) and VolMIP (Volcanic Forcings Model Intercomparison Project)) that have been proposed for inclusion within CMIP were identified as being central to resolving important issues raised at the workshop; for this reason modelling groups were strongly encouraged to participate in these projects. Finally the workshop participants encouraged the WCRP to initiate and support an assessment process lead by the Grand Science Challenge on Clouds, Circulation and Climate Sensitivity on the topic of Earth's Climate Sensitivities, culminating in a report that will be published in 2019, forty years after the seminal report by Charney and co-authors.

Sensitivity↗
NASA NTRS2016

Sensitivity Analysis of the Integrated Medical Model for ISS Programs

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.

medical equipment↗
DOE OSTI2022

Sensitivity Coefficients Calculated for the Prompt Neutron Decay Constant At or Near Delayed Critical

The derivation of a non-invasive prompt neutron decay constant sensitivity coefficient is provided in this work. The computation of the sensitivity coefficient derived in this work does not require modification of Monte Carlo source code and is based on capabilities available in Monte Carlo N-Particle R© Code Version 6.2. The prompt neutron decay constant sensitivity coefficients are calculated for 44-group and 252-group energy structures for specific nuclide-reaction pairs in the Jezebel benchmark experiment. The nuclide-reaction pairs investigated in this work include Pu- 239(n,f), Pu-240(n,f), and Pu-241(n,f). Physical explanations of the sensitivity profiles exhibited by the 252-group energy structure are investigated for the prompt neutron multiplication factor, mean neutron lifetime, and prompt neutron decay constant. The prompt neutron decay constant sensitivity coefficients calculated for the 44-group and 252-group energy structure of Pu-239(n,f) are compared. Lastly, the 44-group energy structure sensitivity coefficients calculated are used for nuclear-data induced uncertainty quantification of the neutron multiplication factor. This work shows that a reduction in the nuclear data-induced uncertainty of the neutron multiplication factor is possible for all nuclide-reaction pairs investigated when prompt neutron decay constant sensitivity coefficients are utilized. This is important for new critical experiment design optimization studies of measurement configurations. This work provides a basis for more detailed sensitivity analysis and uncertainty quantification of nuclide, reaction, and energy-specific cross section data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Modern sensitivity analysis - 15651

Sensitivity analysis has been applied to complex models, such as performance assessment models, since at least the advent of computational tools to support such an approach to model evaluation. Initially, sensitivity analysis methods were applied to deterministic models and focused on changing one input variable at a time. Probabilistic modeling opened the door to evaluating changes in all input variables simultaneously. Standardized rank regression methods were primarily used in the last century to evaluate probabilistic models. These methods assume linearity in the rank response of the model to the inputs. At the very least this assumes monotonicity in the response, but for the most part the response needs to be near-linear. This is highly unlikely for performance assessment models that are based on differential equations, multiplication and division of variables that are usually not correlated, and conservatism that is not well understood. There are better statistical methods for evaluating highly non-linear and dynamic probabilistic models. Some of these methods were founded in the data mining industry. This century has seen a rapid development of the internet that led directly to the development of data mining techniques for massive databases. Although the goals were different, these techniques can be adapted to sensitivity analysis for complex probabilistic models, which, also, form large, or even massive, databases. These modern sensitivity analysis procedures assess the importance of every explanatory variable (input parameters) used in a probabilistic model. In practice, this means that for each endpoint of interest, every explanatory variable in the model is associated with a quantitative measure of importance. For a given explanatory variable, the importance value depends on the endpoint of interest. This global approach to sensitivity analysis allows all levels of interactions to be evaluated, so that the variation in the output can be measured at every level of possible interaction. The effects are collected together during sensitivity analysis processing, and then separated out to attribute the overall contribution of each input parameter to the model output. These global sensitivity analysis procedures have the ability to characterize non-linear and non-monotonic relationships between explanatory variables and endpoints of interest. This is critically important because of the need to characterize complex interactions among multiple explanatory variables in PA models that often have non-linear and non-monotonic effects. The options for sensitivity analysis are fully explored, including an evaluation of several methods when applying them to a well-known complex non-linear non-monotonic model. The results clearly demonstrate the relative benefit of using data mining methods over simple statistical approaches such as standardized rank regression. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Sensitivity Analysis of Hydraulic Head to Locations of Model Boundaries

Sensitivity analysis is an important component of many model activities in hydrology. Numerous studies have been conducted in calculating various sensitivities. Most of these sensitivity analysis focus on the sensitivity of state variables (e.g. hydraulic head) to parameters representing medium properties such as hydraulic conductivity or prescribed values such as constant head or flux at boundaries, while few studies address the sensitivity of the state variables to some shape parameters or design parameters that control the model domain. Instead, these shape parameters are typically assumed to be known in the model. In this study, based on the flow equation, we derive the equation (and its associated initial and boundary conditions) for sensitivity of hydraulic head to shape parameters using continuous sensitivity equation (CSE) approach. These sensitivity equations can be solved numerically in general or analytically in some simplified cases. Finally, the approach has been demonstrated through two examples and the results are compared favorably to those from analytical solutions or numerical finite difference methods with perturbed model domains, while numerical shortcomings of the finite difference method are avoided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model

Abstract The Department of Energy (DOE)’s Energy Exascale Earth System Model (E3SM), including its atmosphere model (EAM), has many relatively new features. In a previous study we conducted a systematic parametric sensitivity analysis for EAM based on short, perturbed parameter ensemble (PPE) simulations, mainly focusing on global mean climate features and metrics. While parameter values in global climate models are generally invariant in space and time, model response to parameters perturbation may vary by regions and climate regimes, which motivates the need to better understand the EAM model behaviors and physics at regional scale and process level. In this study, using the same set of PPE simulations and a similar sensitivity analysis framework, we identify parameters that cause largest sensitivities over different regions and compare model responses in fast atmospheric processes to the parameters across different cloud regimes for several important cloud-related fidelity metrics. We find that cloud forcing has opposite response to some parameters over mid-latitude vs. tropical land. We also analyze how the parametric sensitivity varies as stratocumulus transitions to shallow convection and to deep convection over ocean. Low cloud forcing and shortwave cloud forcing in the subtropical eastern Pacific are most sensitive to the parameters controlling the width of the probability density function (PDF) of the subgrid vertical velocity ( w’ ) ( gamma ) and the damping of the w’ skewness ( c8 ) near the coast but become more sensitive to the parameter affecting the damping of the w’ variance ( c1 ) further offshore. Detailed interpretation of the spatial dependence of parametric sensitivity is provided. We also investigate how the parametric sensitivity evolves with prediction duration. This study improves our process-level understanding of cloud physics and parameterization and provides insights for developing more advanced regime-aware parameterization schemes in global climate model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Inhibition of TRPC3 downregulates airway hyperresponsiveness, remodeling of OVA-sensitized mouse

Airway hyperresponsiveness (AHR), airway remodeling and inflammation are the fundamental pathological alterations that occur in asthma. Transient receptor potential canonical 3 (TRPC3) has been implicated in diverse functions of airway smooth muscle cells (ASMCs) in asthma. However, the underlying mechanisms remain incompletely understood. We investigated the mRNA and protein expression of TRPC3 in ASMCs from normal and OVA-sensitized mouse. And the effects of inhibition or knockdown of TRPC3 with Ethyl-1- (4- (2,3,3-trichloroacrylamide) phenyl) −5 - (trifluoromethyl) -1H -pyrazole -4-carboxylate (Pyr3) and lentiviral shRNA on OVA-sensitized mouse AHR, airway remodeling, circulating inflammatory cytokines, cell proliferation and migration. We found that TRPC3 mRNA and protein expression levels were significantly increased in ASMCs from OVA-sensitized mouse. Inhibiting TRPC3 with continuous subcutaneous administration of Pyr3 decreased enhanced pause (Penh) of OVA-sensitized mouse. Meanwhile, both Pyr3 and lentiviral shRNA treatment of ASMCs in OVA-sensitized mouse significantly decreased their proliferation and migration. These results suggest that TRPC3 plays a critical role in asthma and represents a promising new target for asthma treatment. - Highlights: • Penh, airway remodeling and the gene expression and protein of TRPC3 are increased in OVA-sensitized mice. • Inhibition of TRPC3 suppresses the OVA-sensitized mice Penh and airway remodeling. • Inhibition of TRPC3 decreases OVA-sensitized mice ASMC proliferation and migration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Introduction of a methoxymethyl side chain into p-phenylenediamine attenuates its sensitizing potency and reduces the risk of allergy induction

The strong sensitizing potencies of the most important primary intermediates of oxidative hair dyes, p-phenylenediamine (PPD) and p-toluylenediamine (PTD, i.e. 2-methyl-PPD) are well established. They are considered as the key sensitizers in hair dye allergic contact dermatitis. While modification of their molecular structure is expected to alter their sensitizing properties, it may also impair their color performance. With introduction of a methoxymethyl side chain we found the primary intermediate 2-methoxymethyl-p-phenylenediamine (ME-PPD) with excellent hair coloring performance but significantly reduced sensitizing properties compared to PPD and PTD: In vitro, ME-PPD showed an attenuated innate immune response when analyzed for its protein reactivity and dendritic cell activation potential. In vivo, the effective concentration of ME-PPD necessary to induce an immune response 3-fold above vehicle control (EC3 value) in the local lymph node assay (LLNA) was 4.3%, indicating a moderate skin sensitizing potency compared to values of 0.1 and 0.17% for PPD and PTD, respectively. Finally, assessing the skin sensitizing potency of ME-PPD under consumer hair dye usage conditions through a quantitative risk assessment (QRA) indicated an allergy induction risk negligible compared to PPD or PTD. - Highlights: • Methoxymethyl side chain in p-phenylenediamine reduces its strong skin sensitizing properties. • Reduced protein reactivity and dendritic cell activation. • Reduced skin sensitizing potency in local lymph node assay (LLNA). • Negligible allergy induction risk under hair dye usage conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Primordial black hole dark matter: A quantitative parameter sensitivity comparison across formation mechanisms and particle candidates

Primordial black holes (PBHs) in the asteroid-mass window ( 10 17 – 10 22 g ) can account for all of the dark matter without violating any observational constraint, yet are routinely dismissed as fine-tuned. I put that dismissal to the test by applying three complementary sensitivity measures uniformly across a broad landscape: three noninflationary PBH production mechanisms, six classes of inflationary PBH models, and seven particle dark matter benchmarks, all evaluated against the same observable target. Three distinct naturalness universality classes emerge, determined entirely by the analytic structure of the abundance map rather than by the nature of the dark matter candidate. Biased-domain-wall PBHs, in their least model-dependent (free- V b ) form, have the same low sensitivity, Δ = 4.5 , as off-resonance weakly interacting massive particles and freeze-in particles ( Δ = 2 ), a sensitivity that, because it is constant over the entire parameter space of the construction, also coincides trivially with its own Wilson-normalized average within that parameter space (Section Definition and conventions), an equivalence that concerns only the space over which Δ is computed and is not a naturalness statement about the construction as a whole; a further reduction to Δ = 2 is possible only under the additional, independently motivated but not required, assumption that the domain-wall bias is generated by Planck-suppressed operators; early matter-domination PBHs occupy an intermediate tier alongside coannihilating weakly interacting massive particles (WIMPs), unified by a structural identity in which the sensitivity measure equals the logarithm of the ratio of the formation scale to the matter–radiation equality scale; first-order phase transition PBHs, once the more accurate super-exponential collapse probability is used in place of the single-exponential approximation, instead belong to the same highly sensitive tier as resonant WIMP annihilation and single-field inflationary collapse, for a structurally distinct reason; single-field ultraslow-roll inflationary collapse is severely tuned for a distinct reason: a double exponential in which the power spectrum amplitude is itself exponentially sensitive to the inflaton potential coefficients, on top of the exponential collapse sensitivity of the abundance map. My main conclusion is that the claim that PBH dark matter is generically fine-tuned conflates the worst case with a landscape spanning every naturalness tier. The Barbieri-Giudice sensitivity computed here and the Wilson-normalized measure of Iovino and Riotto answer distinct and mutually consistent questions about the same construction, a distinction I clarify within the two-layer decomposition.

Profumo, Stefano [University of California, Santa ↗