Search NASA⌕ Search

SEARCH · Search NASA

Results for “Concorde”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Strong Correspondence in Evapotranspiration and Carbon Dioxide Fluxes Between Different Eddy Covariance Systems Enables Quantification of Landscape Heterogeneity in Dryland Fluxes

Abstract The eddy covariance method is widely used to investigate fluxes of energy, water, and carbon dioxide at landscape scales, providing important information on how ecological systems function. Flux measurements quantify ecosystem responses to environmental perturbations and management strategies, including nature‐based climate‐change mitigation measures. However, due to the high cost of conventional instrumentation, most eddy covariance studies employ a single system, limiting spatial representation to the flux footprint. Insufficient replication may be limiting our understanding of ecosystem behavior. To address this limitation, we deployed eight lower‐cost eddy covariance systems in two clusters around two conventional eddy covariance systems in the Chihuahuan Desert of North America for a period of 2 years. These dryland settings characterized by large temperature variations and relatively low carbon dioxide fluxes represented a challenging setting for eddy covariance. We found very good closure of energy and water balance across all systems (within ±9% of unity). We found very good correspondence between the lower‐cost and conventional systems' fluxes of sensible heat (with concordance correlation coefficient (CCC) of ≥0.87), latent energy (evapotranspiration; CCC ≥ 0.89), and useful correspondence in the net ecosystem exchange ((NEE); with CCC ≥ 0.4) at the daily temporal resolution. Relative to the conventional systems, the low‐frequency systems were characterized by a higher level of random error, particularly in the NEE fluxes. Lower‐cost systems can enable wider deployment affording better replication and sampling of spatiotemporal variability at the expense of greater measurement noise that might be limiting for certain applications. Replicated eddy covariance observations may be useful when addressing gaps in the existing monitoring of critical and underrepresented ecosystems and for measuring areas larger than a single flux footprint.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Estimating Soil Thermal Inertia Profiles From the Passive Equilibration of a Temperature Probe

Knowledge of the distribution of soil thermal properties is important for understanding subsurface hydrological and biogeochemical processes. This study describes and evaluates quick thermal profiling (QTP), a new measurement technique aimed at providing rapid, depth-resolved measurements of soil thermal inertia at numerous locations across the landscape. A cylindrical probe with temperature sensors at multiple depths is quickly inserted into the ground, and soil thermal inertia is estimated from how quickly the probe temperature equilibrates with the soil. To this end, a finite volume heat transfer model is used to generate temperature equilibration time series across combinations of controlling factors, and a gridded search inversion approach is applied to infer soil thermal inertia. Field tests in the Arctic indicate that QTP measurements have a minimum uncertainty of 0.14 J m −2 K −1 s −1/2 and covary with dual-probe heat pulse thermal analyzer measurements (concordance correlation coefficient = 0.56) with a root-mean-square error of 0.40 J m −2 K −1 s −1/2 . Besides demonstrating the value of QTP for estimating thermal inertia, this study identifies various sources of measurement uncertainty, particularly probe-soil contact resistance and frictional heating. Further, analysis of soil samples indicates that thermal inertia can be used to estimate thermal conductivity and dry bulk density in the studied area, although such inferences are highly site-specific. Overall, the QTP method holds promise to generate thermal inertia data products and to complement other characterization approaches for advancing understanding of soil properties across far more locations than is currently possible.

Lamb, J. R. [Lawrence Berkeley National Laboratory↗
DOE OSTI2022

A functional map of HIV-host interactions in primary human T cells

Human Immunodeficiency Virus (HIV) relies on host molecular machinery for replication. Systematic attempts to genetically or biochemically define these host factors have yielded hundreds of candidates, but few have been functionally validated in primary cells. Here, we target 426 genes previously implicated in the HIV lifecycle through protein interaction studies for CRISPR-Cas9-mediated knock-out in primary human CD4+ T cells in order to systematically assess their functional roles in HIV replication. We achieve efficient knockout (>50% of alleles) in 364 of the targeted genes and identify 86 candidate host factors that alter HIV infection. 47 of these factors validate by multiplex gene editing in independent donors, including 23 factors with restrictive activity. Both gene editing efficiencies and HIV-1 phenotypes are highly concordant among independent donors. Importantly, over half of these factors have not been previously described to play a functional role in HIV replication, providing numerous novel avenues for understanding HIV biology. These data further suggest that host-pathogen protein-protein interaction datasets offer an enriched source of candidates for functional host factor discovery and provide an improved understanding of the mechanics of HIV replication in primary T cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Entire expressed peripheral blood transcriptome in pediatric severe malarial anemia

Abstract This study on severe malarial anemia (SMA: Hb < 6.0 g/dL), a leading global cause of childhood morbidity and mortality, compares the entire expressed whole blood host transcriptome between Kenyan children (3-48 mos.) with non-SMA (Hb ≥ 6.0 g/dL, n = 39) and SMA ( n = 18). Differential expression analyses reveal 1403 up-regulated and 279 down-regulated transcripts in SMA, signifying impairments in host inflammasome activation, cell death, and innate immune and cellular stress responses. Immune cell profiling shows decreased memory responses, antigen presentation, and immediate pathogen clearance, suggesting an immature/improperly regulated immune response in SMA. Module repertoire analysis of blood-specific gene signatures identifies up-regulation of erythroid genes, enhanced neutrophil activation, and impaired inflammatory responses in SMA. Enrichment analyses converge on disruptions in cellular homeostasis and regulatory pathways for the ubiquitin-proteasome system, autophagy, and heme metabolism. Pathway analyses highlight activation in response to hypoxic conditions [Hypoxia Inducible Factor (HIF)−1 target and Reactive Oxygen Species (ROS) signaling] as a central theme in SMA. These signaling pathways are also top-ranking in protein abundance measures and a Ugandan SMA cohort with available transcriptomic data. Targeted RNA-Seq validation shows strong concordance with our entire expressed transcriptome data. These findings identify key molecular themes in SMA pathogenesis, offering potential targets for new malaria therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Genome-resolved biogeography of Phaeocystales, cosmopolitan bloom-forming algae

Phaeocystales, comprising the genus Phaeocystis and an uncharacterized sister lineage, are nanoplanktonic haptophytes widespread in the global ocean. Several species form mucilaginous colonies and influence key biogeochemical cycles, yet their underlying diversity and ecological strategies remain underexplored. Here, we present new genomic data from 13 strains, including three high-quality reference genomes (N50 > 30 kbp), and integrate previous metagenome-assembled genomes to resolve a robust phylogeny. Divergence timing of P. antarctica aligns with Miocene cooling and Southern Ocean isolation. Genomic traits reveal metabolic flexibility, including mixotrophic nitrogen acquisition in temperate waters and gene expansions linked to polar nutrient adaptation. Concordantly, transcriptomic comparisons between temperate and polar Phaeocystis suggest Southern Ocean populations experience iron and B12 limitation. We also identify signatures of horizontal gene transfer and endogenous giant virus/virophage insertions. Together, these findings highlight Phaeocystales as an ecologically versatile and geographically widespread lineage shaped by evolutionary innovation and adaptation to contrasting environmental stressors.

Füssy, Zoltán↗
DOE OSTI2023

Ocean current patterns drive the worldwide colonization of eelgrass (Zostera marina)

Currents are unique drivers of oceanic phylogeography and thus determine the distribution of marine coastal species, along with past glaciations and sea-level changes. Here we reconstruct the worldwide colonization history of eelgrass (Zostera marina L.), the most widely distributed marine flowering plant or seagrass from its origin in the Northwest Pacific, based on nuclear and chloroplast genomes. We identified two divergent Pacific clades with evidence for admixture along the East Pacific coast. Two west-to-east (trans-Pacific) colonization events support the key role of the North Pacific Current. Time-calibrated nuclear and chloroplast phylogenies yielded concordant estimates of the arrival of Z. marina in the Atlantic through the Canadian Arctic, suggesting that eelgrass-based ecosystems, hotspots of biodiversity and carbon sequestration, have only been present there for ~243 ky (thousand years). Mediterranean populations were founded ~44 kya, while extant distributions along western and eastern Atlantic shores were founded at the end of the Last Glacial Maximum (~19 kya), with at least one major refuge being the North Carolina region. The recent colonization and five- to sevenfold lower genomic diversity of the Atlantic compared to the Pacific populations raises concern and opportunity about how Atlantic eelgrass might respond to rapidly warming coastal oceans.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multiomics and deep learning dissect regulatory syntax in human development

Transcription factors establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility and regulating gene expression1. Mapping accessible chromatin offers critical insights into transcriptional control, but available datasets for human development are restricted to bulk tissue, single organs or single modalities2. Here we present the Human Development Multiomic Atlas, a single-cell atlas of chromatin accessibility and gene expression from 817,740 fetal cells across 12 organs, spanning 203 cell types and more than 1 million candidate cis-regulatory elements, many of which exhibit organ-specific in vivo enhancer activity. Deep learning models trained to predict accessibility from local DNA sequence unravel a comprehensive lexicon of motifs that influence accessibility, including composite motifs exhibiting distinct syntactic constraints that are predicted to mediate transcription factor cooperativity. We identify ‘hard’ syntactic rules requiring precise motif spacing and orientation, ‘soft’ rules allowing flexible motif arrangements, and ubiquitous motifs inhibiting accessibility. Model-based interpretation of genetic variants reveals that disruption of motifs with positive and negative effects is associated with concordant effects on gene expression. Our work delineates how motif syntax governs cell-type-specific chromatin accessibility and provides a foundational resource for decoding cis-regulatory logic and interpreting genetic variation during human development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Machine learning for endoleak detection after endovascular aortic repair

Diagnosis of endoleak following endovascular aortic repair (EVAR) relies on manual review of multi-slice CT angiography (CTA) by physicians which is a tedious and time-consuming process that is susceptible to error. We evaluate the use of a deep neural network for the detection of endoleak on CTA for post-EVAR patients using a novel data efficient training approach. 50 CTAs and 20 CTAs with and without endoleak respectively were identified based on gold standard interpretation by a cardiovascular subspecialty radiologist. The Endoleak Augmentor, a custom designed augmentation method, provided robust training for the machine learning (ML) model. Predicted segmentation maps underwent post-processing to determine the presence of endoleak. The model was tested against 3 blinded general radiologists and 1 blinded subspecialist using a held-out subset (10 positive endoleak CTAs, 10 control CTAs). Model accuracy, precision and recall for endoleak diagnosis were 95%, 90% and 100% relative to reference subspecialist interpretation (AUC = 0.99). Accuracy, precision and recall was 70/70/70% for generalist1, 50/50/90% for generalist2, and 90/83/100% for generalist3. The blinded subspecialist had concordant interpretations for all test cases compared with the reference. In conclusion, our ML-based approach has similar performance for endoleak diagnosis relative to subspecialists and superior performance compared with generalists.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Long-term survival and second malignant tumor prediction in pediatric, adolescent, and young adult cancer survivors using Random Survival Forests: a SEER analysis

Abstract Survival and second malignancy prediction models can aid clinical decision making. Most commonly, survival analysis studies are performed using traditional proportional hazards models, which require strong assumptions and can lead to biased estimates if violated. Therefore, this study aims to implement an alternative, machine learning (ML) model for survival analysis: Random Survival Forest (RSF). In this study, RSFs were built using the U.S. Surveillance Epidemiology and End Results to (1) predict 30-year survival in pediatric, adolescent, and young adult cancer survivors; and (2) predict risk and site of a second tumor within 30 years of the first tumor diagnosis in these age groups. The final RSF model for pediatric, adolescent, and young adult survival has an average Concordance index (C-index) of 92.9%, 94.2%, and 94.4% and average time-dependent area under the receiver operating characteristic curve (AUC) at 30-years since first diagnosis of 90.8%, 93.6%, 96.1% respectively. The final RSF model for pediatric, adolescent, and young adult second malignancy has an average C-index of 86.8%, 85.2%, and 88.6% and average time-dependent AUC at 30-years since first diagnosis of 76.5%, 88.1%, and 99.0% respectively. This study suggests the robustness and potential clinical value of ML models to alleviate physician burden by quickly identifying highest risk individuals.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Deficiency in PHD2-mediated hydroxylation of HIF2α underlies Pacak-Zhuang syndrome

Pacak-Zhuang syndrome is caused by mutations in the EPAS1 gene, which encodes for one of the three hypoxia-inducible factor alpha (HIFα) paralogs HIF2α and is associated with defined but varied phenotypic presentations including neuroendocrine tumors and polycythemia. However, the mechanisms underlying the complex genotype-phenotype correlations remain incompletely understood. Here, we devised a quantitative method for determining the dissociation constant (K d ) of the HIF2α peptides containing disease-associated mutations and the catalytic domain of prolyl-hydroxylase (PHD2) using microscale thermophoresis (MST) and showed that neuroendocrine-associated Class 1 HIF2α mutants have distinctly higher K d than the exclusively polycythemia-associated Class 2 HIF2α mutants. Based on the co-crystal structure of PHD2/HIF2α peptide complex at 1.8 Å resolution, we showed that the Class 1 mutated residues are localized to the critical interface between HIF2α and PHD2, adjacent to the PHD2 active catalytic site, while Class 2 mutated residues are localized to the more flexible region of HIF2α that makes less contact with PHD2. Concordantly, Class 1 mutations were found to significantly increase HIF2α-mediated transcriptional activation in cellulo compared to Class 2 counterparts. These results reveal a structural mechanism in which the strength of the interaction between HIF2α and PHD2 is at the root of the general genotype-phenotype correlations observed in Pacak-Zhuang syndrome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Biomass-Derived Polymeric Binders in Silicon Anodes for Battery Energy Storage Applications

The demand for portable electronic devices has increased rapidly during the past decade, and has driven a concordant growth in battery production. Since their development as a commercial energy storage solution in the 1990s, lithium-ion batteries (LIBs) have attracted significant attention in both science and industry due to their long cycle life, high energy density, low self-discharge rate, and high working voltage. Production of LIBs requires large amounts of a polymeric binder – commonly polyvinylidene difluoride (PVDF) – for processing and performance purposes. However, since this material is petrochemically-derived, it is far from “green” or sustainable. On the other hand, polymers and their building blocks are found widely throughout nature and can be renewably sourced from biomass at low cost; therefore, replacing PVDF with biomass-derived binders is a promising approach to reduce the environmental footprint of LIBs. Additionally, polymer binders play a critical role in next-generation battery performance. For instance, silicon (Si) is a promising high-capacity anode material for LIBs because of its high theoretical capacity (4200 mA h g –1 ), low working potential, and high abundance in Earth's crust. However, its huge volume change during charge/discharge tends to result in a shortened cycle life, since conventional binders interact only weakly with silicon's native surface and cannot maintain long-term integrity of the electrode. Naturally derived polymers have found better success in this role due to their high structural advantages. In this review, we summarize recent developments in silicon anode binders derived from various biomass sources, with a focus on polymer properties and their effect on battery performance. Further, we propose various perspectives based on our own assessment of these works, and provide a brief commentary on the future outlook of the field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The impact of new d(p,γ)3 rates on Big Bang Nucleosynthesis

We consider the effect on Big Bang Nucleosynthesis (BBN) of new measurements of the d(p,γ) 3 He cross section by the LUNA Collaboration. These have an important effect on the primordial abundance of D/H which is also sensitive to the baryon density at the time of BBN. We have re-evaluated the thermal rate for this reaction, using a world average of cross section data, which we describe with model-independent polynomials; our results are in good agreement with a similar analysis by LUNA. We then perform a full likelihood analysis combining BBN and Planck cosmic microwave background (CMB) likelihood chains using the new rate combined with previous measurements and compare with the results using previous rates. Concordance between BBN and CMB measurements of the anisotropy spectrum using the old rates was excellent. The predicted deuterium abundance at the Planck value of the baryon density was (D/H) BBN+CMB old = (2.57 ± 0.13) × 10 –5 which can be compared with the value determined from quasar absorption systems (D/H) obs = (2.55 ± 0.03) × 10 –5 . Using the new rates we find (D/H) BBN+CMB = (2.51 ± 0.11) × 10 –5 . We thus find consistency among BBN theory, deuterium and 4He observations, and the CMB, when using reaction rates fit in our data-driven approach. We also find that the new reaction data tightens the constraints on the number of relativistic degrees of freedom during BBN, giving the effective number of light neutrino species N ν = 2.880 ± 0.144 in good agreement with the Standard Model of particle physics. Lastly, we note that the observed deuterium abundance continues to be more precise than the BBN+CMB prediction, whose error budget is now dominated by d(d,n) 3 He and d(d,p) 3 H.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Implications of the non-observation of 6 Li in halo stars for the primordial 7 Li problem

The primordial Lithium Problem is intimately connected to the assumption that the 7 Li abundance observed in metal-poor halo stars is unchanged from its primordial value, which lies significantly below the predictions of standard big-bang nucleosynthesis. Two key lines of evidence have argued that these stars have not significantly depleted their initial (mostly primordial) 7 Li: i) the lack of dispersion in Li abundance measurements at low metallicity (and high surface temperature); and ii) the detection of the more fragile 6 Li isotope in at least two halo stars. The purported 6 Li detections were in good agreement with predictions from cosmic-ray nucleosynthesis which is responsible for the origin of 6 Li. This concordance left little room for 6 Li depletion, and the apparent 6 Li survival implied that 7 Li largely evaded destruction, because stellar interiors destroy 6 Li more vigorously then than 7 Li. Recent (re)-observations of halo stars challenge the evidence against 7 Li depletion: i) lithium elemental abundances now show significant dispersion, and ii) sensitive 6 Li searches now reveal only upper limits to the 6 Li/ 7 Li ratio. We discuss the consequences of these 6 Li non-detections on the primordial 7 Li Problem, Galactic cosmic-ray nucleosynthesis, and the question of differential depletion of Li in stars. The tight new 6 Li upper limits generally fall far below the predictions of cosmic-ray nucleosynthesis, implying that substantial 6 Li depletion has occurred — by factors up to 50. We show that in stars with 6 Li limits and thus lower bounds on 6 Li depletion, an equal amount of 7 Li depletion is more than sufficient to resolve the primordial 7 Li Problem. This picture is consistent with well-studied stellar models in which 7 Li is less depleted than 6 Li, and strengthen the case that the Lithium Problem has an astrophysical solution. We conclude by suggesting future observations that could test these ideas.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

What is flat ΛCDM, and may we choose it?

The Universe is neither homogeneous nor isotropic, but it is close enough that we can reasonably approximate it as such on suitably large scales. The inflationary-Λ-Cold Dark Matter (ΛCDM) concordance cosmology builds on these assumptions to describe the origin and evolution of fluctuations. With standard assumptions about stress-energy sources, this system is specified by just seven phenomenological parameters, whose precise relations to underlying fundamental theories are complicated and may depend on details of those fields. Nevertheless, it is common practice to set the parameter that characterizes the spatial curvature, Ω K , exactly to zero. This parameter-fixed ΛCDM is awarded distinguished status as separate model, "flat ΛCDM." Ipso facto this places the onus on proponents of "curved ΛCDM" to present sufficient evidence that Ω K ≠ 0, and is needed as a parameter. While certain inflationary model Lagrangians, with certain values of their parameters, and certain initial conditions, will lead to a present-day universe well-described as containing zero curvature, this does not justify distinguishing that subset of Lagrangians, parameters and initial conditions into a separate model. Absent any theoretical arguments, we cannot use observations that suggest small Ω K to enforce Ω K = 0. Our track record in picking inflationary models and their parameters a priori makes such a choice dubious, and concerns about tensions in cosmological parameters and large-angle cosmic-microwave-background anomalies strengthens arguments against this choice. We argue that Ω K must not be set to zero, and that ΛCDM remains a phenomenological model with at least 7 parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Limits on non-relativistic matter during Big-bang nucleosynthesis

Big-bang nucleosynthesis (BBN) probes the cosmic mass-energy density at temperatures ~10 MeV to ~100 keV. Here, we consider the effect of a cosmic matter-like species that is non-relativistic and pressureless during BBN. Such a component must decay; doing so during BBN can alter the baryon-to-photon ratio, η, and the effective number of neutrino species. We use light element abundances and the cosmic microwave background (CMB) constraints on η and N ν to place constraints on such a matter component. We find that electromagnetic decays heat the photons relative to neutrinos, and thus dilute the effective number of relativistic species to N eff < 3 for the case of three Standard Model neutrino species. Intriguingly, likelihood results based on Planck CMB data alone find N ν = 2.800 ± 0.294, and when combined with standard BBN and the observations of D and 4 He give N ν = 2.898 ± 0.141. While both results are consistent with the Standard Model, we find that a nonzero abundance of electromagnetically decaying matter gives a better fit to these results. Our best-fit results are for a matter species that decays entirely electromagnetically with a lifetime τ X = 0.89 sec and pre-decay density that is a fraction ξ = (ρ X /ρ rad |10 MeV = 0.0026 of the radiation energy density at 10 MeV; similarly good fits are found over a range where ξτ X 1/2 is constant. On the other hand, decaying matter often spoils the BBN+CMB concordance, and we present limits in the (τ X ,ξ) plane for both electromagnetic and invisible decays. For dark (invisible) decays, standard BBN (i.e. ξ = 0) supplies the best fit. We end with a brief discussion of the impact of future measurements including CMB-S4.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Myosin dilated cardiomyopathy mutation S532P disrupts actomyosin interactions, leading to altered muscle kinetics, reduced locomotion, and cardiac dilation in Drosophila

Dilated cardiomyopathy (DCM), a life-threatening disease characterized by pathological heart enlargement, can be caused by myosin mutations that reduce contractile function. To better define the mechanistic basis of this disease, we employed the powerful genetic and integrative approaches available in Drosophila melanogaster. To this end, we generated and analyzed the first fly model of human myosin–induced DCM. The model reproduces the S532P human β-cardiac myosin heavy chain DCM mutation, which is located within an actin-binding region of the motor domain. In concordance with the mutation’s location at the actomyosin interface, steady-state ATPase and muscle mechanics experiments revealed that the S532P mutation reduces the rates of actin-dependent ATPase activity and actin binding and increases the rate of actin detachment. The depressed function of this myosin form reduces the number of cross-bridges during active wing beating, the power output of indirect flight muscles, and flight ability. Further, S532P mutant hearts exhibit cardiac dilation that is mutant gene dose–dependent. Our study shows that Drosophila can faithfully model various aspects of human DCM phenotypes and suggests that impaired actomyosin interactions in S532P myosin induce contractile deficits that trigger the disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma

Abstract Background Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managing patients. Objectives To determine if artificial intelligence and machine learning might help to stratify patients with cSCC by risk using more than solely clinical and histopathological factors. Methods We retrieved a retrospective cohort of 104 patients whose cSCCs had been excised with clear margins. Clinical and histopathological risk factors were evaluated. Haematoxylin and eosin-stained slides were scanned and analysed by an algorithm based on the stacked predictive sparse decomposition technique. Cellular morphometric biomarkers (CMBs) were identified via machine learning and used to derive a cellular morphometric risk score (CMRS) that classified cSCCs into clusters of differential prognoses. Concordance analysis, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated and compared with results obtained with the Brigham and Women’s Hospital (BWH) staging system. The performance of the combination of the BWH staging system and the CMBs was also analysed. Results There were no differences among the CMRS groups in terms of clinical and histopathological risk factors and T-stage assignment, but there were significant differences in prognosis. Combining the CMRS with BWH staging systems increased distinctiveness and improved prognostic performance. C-indices were 0.91 local recurrence and 0.91 for nodal metastasis when combining the two approaches. The NPV was 94.41% and 96.00%, the PPV was 36.36% and 41.67%, and accuracy reached 86.75% and 89.16%, respectively, with the combined approach. Conclusions CMRS is helpful for cSCC risk stratification beyond classic clinical and histopathological risk features. Combining the information from the CMRS and the BWH staging system offers outstanding prognostic performance for patients with high-risk cSCC.

Pérez-Baena, Manuel J.↗
DOE OSTI2025

Enantioselective ecotoxicity of promethazine in two freshwater organisms: daphnia (Daphnia magna) and zebrafish ( Danio rerio )

Abstract Chiral pharmaceuticals, racemic or enantiomerically pure forms and their metabolites, can reach aquatic ecosystems via wastewater effluents (inefficient treatment operations) or by direct human disposal. They may negatively affect nontarget organisms even at low environmental concentrations. To make an accurate risk evaluation, the (eco)toxicity of both enantiomers needs to be assessed. Promethazine (PMZ) is a chiral antihistamine that has been detected in aquatic ecosystems owing to its high consumption. Promethazine undergoes metabolism in the liver, producing chiral metabolites such as promethazine sulfoxide (PMZSO) and N-desmethylpromethazine (DMPMZ) that reach water bodies. However, knowledge regarding the enantioselective toxicity of PMZ and its metabolites on aquatic organisms is missing. This study aimed to explore the potential enantioselective toxicity of PMZ and its metabolites on two relevant freshwater organisms, daphniid and fish, representing different trophic levels. The half maximal effect concentrations (EC50s) in Daphnia magna of PMZ, DMPMZ, and PMZSO were 2.33, 2.31, > 4 mg L−1, respectively, > 4 and 2.50 mg L−1 for (R) and (S)-PMZ, respectively, and > 4 mg L−1 for the enantiomers of DMPMZ and PMZSO. In studies involving zebrafish, Danio rerio, (R, S)-PMZ showed a median lethal concentration (LC50) of .72 mg L−1, and specific assays revealed that (R)-PMZ exhibited more pronounced adverse effects on larvae at the embryonic, morphological, and biochemical level than the racemate and (S)-PMZ. Toxicity and potential bioaccumulation of these compounds in daphniids and fish were also conducted using in silico tests through proprietary software. The results revealed a concordance between the experimental and predicted EC50 and LC50 values in both species.

Coelho, Maria Miguel↗