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Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components: A Reactor Coolant Pump Use Case

This work develops data-driven models for onset of thermal barrier leakage in reactor coolant pumps. It incorporates uncertainty quantification to enhance the reliability and robustness of pre- dictions. Using synthetic data generated by the Generic Pressurized Water Reactor simulator, realistic degradation scenarios were simulated across lifecycle stages—beginning, middle, and end of life. Key variables, including differential pressure, flow rate, vibration, and temperatures, were analyzed using machine learning framework. The fully connected neural network models demonstrated exceptional performance, achieving R2 scores exceeding 0.99 and root mean square errors as low as around 8.23 × 10-2 gallon per minute (gpm) for the three stages of the lifecy- cle. UQ analysis further validated the model’s robustness, with narrow uncertainty bounds during steady-state operations and appropriately wider bounds during transitional phases, reflecting the physical behavior of the system. This work addresses important gaps in real-time condition moni- toring and regulatory compliance by integrating advanced condition monitoring technologies with UQ into IST programs. The ability to detect thermal barrier leakage early and quantify prediction reliability supports optimizing maintenance strategies while ensuring nuclear power plants’ safe and reliable operation.

99 - GENERAL AND MISCELLANEOUS↗

Bringing weak transitions to light

Abstract Weak transitions between quantum states are of fundamental importance for a broad range of phenomena from analytical biochemistry to precision physics, but generally challenge experimental detection. Due to their small cross sections scaling with the absolute square of their transition matrix elements, spectroscopic measurements often fail in particular in the presence of competing background processes. Here we introduce a general concept to break this scaling law and enhance the transition probability by exploiting a stronger laser-coupled pathway to the same excited state. We demonstrate the concept experimentally by attosecond transient absorption spectroscopy in helium atoms. The quasi-forbidden transitions from the ground state 1s 2 to the weakly coupled doubly excited 2p3dandsp 2,4− states are boosted by an order of magnitude. Enhancing single-photon-suppressed transitions can find widespread applicability, from spectral diagnostics of complex molecules in life and chemical sciences to precision spectroscopy of weak transitions in metastable atomic nuclei in the search for new physics.

Science & Technology - Other Topics↗

Laser Powder Bed Fusion Manufactured Alloys 625 and 282 and Properties Relevant to Advanced Nuclear Components

Under the Advanced Materials and Manufacturing Technologies program, two Ni-based alloys fabricated by laser powder bed fusion (LPBF) have been evaluated: γ′-strengthened Haynes 282 and solution-strengthened Inconel 625. Large printing defects were observed in the LPBF 282 alloy fabricated using a Renishaw AM250 machine, likely due to particle spattering during printing. Annealing at 1,180°C for 1 h followed by 4 h at 800°C in a high density of 50 nm γ′-strengthening precipitates as well as partial recrystallization resulted in a bimodal grain distribution. Creep testing performed at 750°C revealed lower creep life and ductility for the LPBF 282 compared with wrought 282. X-ray computed tomography combined with optical and scanning electron microscopy microstructural characterization revealed crack formation during creep testing, initiated either from printing defects or from creep cavitation at grain boundaries. Printing defects were the likely reason for the lower creep performance of LPBF 282 and could be suppressed by optimizing the build configuration. Printing 625 on an EOS M290 machine using the recommended EOS parameters resulted in a very low defect density. Superior creep strength at 725°C was observed for the as-printed LPBF 625 along the build direction when compared with wrought 625. No defect larger than ~50 µm could be detected by X-ray computed tomography in the as-printed conditions and after creep testing for 1,000 h at 725°C and 150 MPa. Small, needle-like δ-phase precipitates were observed after creep testing for 100 h at 725°C and 200 MPa. The rapid formation of the γ phase is directly related to the initial Nb and Mo segregation in the LPBF 625 cell walls, and its effect on the alloy’s high-temperature performance will be evaluated. Solution annealing was carried out at 1,150°C for 1 h and led to full recrystallization of the alloy. A decrease in strength and increase in ductility were observed after solution annealing, and the alloy recrystallization resulted in isotropic tensile properties at room temperature, contrary to what was observed for the as-printed LPBF 625.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Performance Evaluation of Weather@home2 Simulations over West African Region

Weather and climate forecasting, using climate models, have become essential tools and life-savers in the West African region; in spite of the fact that climate models do not fully comply with attributes of forecast qualities—RASAP: reliability, association, skill, accuracy, and precision. The objective of this paper is to quantitatively evaluate, in comparison to CRU and ERA5 datasets, the RASAP compliance-level of the weather@home2 modeling system (w@h2). Findings from some statistical evaluations show that, to a moderately significant extent, w@h2 model provides useful information during the monsoon seasons; skills to capture the Little Dry Season over the Guinea zone; predictive skills for the onset season; ability to reproduce all the annual characteristics of the surface maximum air temperature over the region; as well as skill to detect heat waves that usually ravage West Africa during the boreal spring. The model displays traces of attributes that are needed for seasonal climate predictions and applications. Deficiencies in the quantitative reproducibility point to the facts that the model does provide a reliability akin to that of regional climate models. This paper further furnishes a prospective user with information on whether the model might be “useful or not” for a particular application.

West Africa↗

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗

Label-Free In Situ Chemical Characterization of Amyloid Plaques in Human Brain Tissues

The accumulation of amyloid plaques and increased brain redox burdens are neuropathological hallmarks of Alzheimer’s disease. Altered metabolism of essential biometals is another feature of Alzheimer’s, with amyloid plaques representing sites of disturbed metal homeostasis. Despite these observations, metal-targeting disease treatments have not been therapeutically effective to date. A better understanding of amyloid plaque composition and the role of the metals associated with them is critical. To establish this knowledge, the ability to resolve chemical variations at nanometer length scales relevant to biology is essential. Here, we present a methodology for the label-free, nanoscale chemical characterization of amyloid plaques within human Alzheimer’s disease tissue using synchrotron X-ray spectromicroscopy. Our approach exploits a C–H carbon absorption feature, consistent with the presence of lipids, to visualize amyloid plaques selectively against the tissue background, allowing chemical analysis to be performed without the addition of amyloid dyes that alter the native sample chemistry. Using this approach, we show that amyloid plaques contain elevated levels of calcium, carbonates, and iron compared to the surrounding brain tissue. Chemical analysis of iron within plaques revealed the presence of chemically reduced, low-oxidation-state phases, including ferromagnetic metallic iron. The zero-oxidation state of ferromagnetic iron determines its high chemical reactivity and so may contribute to the redox burden in the Alzheimer’s brain and thus drive neurodegeneration. Ferromagnetic metallic iron has no established physiological function in the brain and may represent a target for therapies designed to lower redox burdens in Alzheimer’s disease. Additionally, ferromagnetic metallic iron has magnetic properties that are distinct from the iron oxide forms predominant in tissue, which might be exploitable for the in vivo detection of amyloid pathologies using magnetically sensitive imaging. We anticipate that this label-free X-ray imaging approach will provide further insights into the chemical composition of amyloid plaques, facilitating better understanding of how plaques influence the course of Alzheimer’s disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automation for Electric Vehicle Battery Pack Disassembly

Battery‐electric vehicles (EVs) are growing exponentially. The demand for these batteries is expected to increase sevenfold by 2035. The EV batteries reach their end of life when the capacity fades to 70%–80% of new, with some being removed from the primary applications with even lower levels of degradation. These batteries can be used in less demanding applications. The disassembly process is currently manual, slow, unsafe, and expensive. Automation is needed to increase the throughput. EV battery packs feature various continually changing designs and form factors, which limit the usefulness of deterministically programmed robotic solutions. The conceptual robotic disassembly of EV batteries has attracted the attention of researchers. However, while many approaches have been proposed, practical implementations are lacking. Here, we review proposed concepts for EV battery disassembly and describe the selected approach, with elements of partial solutions validated in a laboratory setting, including the selection of commercial solutions, the development of custom end effectors, and methodologies for detection, localization, and classification of fasteners. The computer vision tasks employed an overhead 2D camera to detect the type of battery pack and approximate localization of fasteners, and a 3D camera mounted on the robotic arm for precise localization (position and tilt) and classification.

Islam, Abu [Rochester Inst. of Technology, Rochest↗

Rev1 overexpression accelerates N -methyl- N -nitrosourea (MNU)-induced thymic lymphoma by increasing mutagenesis

Rev1 has two important functions in the translesion synthesis pathway, including dCMP transferase activity, and acts as a scaffolding protein for other polymerases involved in translesion synthesis. However, the role of Rev1 in mutagenesis and tumorigenesis in vivo remains unclear. We previously generated Rev1-overexpressing (Rev1-Tg) mice and reported that they exhibited a significantly increased incidence of intestinal adenoma and thymic lymphoma (TL) after N-methyl-N-nitrosourea (MNU) treatment. In this study, we investigated mutagenesis of MNU-induced TL tumorigenesis in wild-type (WT) and Rev1-Tg mice using diverse approaches, including whole-exome sequencing (WES). In Rev1-Tg TLs, the mutation frequency was higher than that in WT TL in most cases. However, no difference in the number of nonsynonymous mutations in the Catalogue of Somatic Mutations in Cancer (COSMIC) genes was observed, and mutations involved in Notch1 and MAPK signaling were similarly detected in both TLs. Mutational signature analysis of WT and Rev1-Tg TLs revealed cosine similarity with COSMIC mutational SBS5 (aging-related) and SBS11 (alkylation-related). Interestingly, the total number of mutations, but not the genotypes of WT and Rev1-Tg, was positively correlated with the relative contribution of SBS5 in individual TLs, suggesting that genetic instability could be accelerated in Rev1-Tg TLs. Finally, we demonstrated that preleukemic cells could be detected earlier in Rev1-Tg mice than in WT mice, following MNU treatment. In conclusion, Rev1 overexpression accelerates mutagenesis and increases the incidence of MNU-induced TL by shortening the latency period, which may be associated with more frequent DNA damage-induced genetic instability.

60 APPLIED LIFE SCIENCES↗

Vivianite oxidation is not photocatalyzed

Vivianite is a hydrous Fe2+ phosphate mineral found in anoxic environments that plays an integral role in P cycling and environmental biogeochemistry. Imbued in the vivianite literature dating as far back as 1918 is the notion that vivianite is light-sensitive and susceptible to rapid photooxidation induced entirely by solar light. However, despite an exhaustive search, to our knowledge this conventionally accepted assumption has never been directly tested, nor has the band gap ever been measured. Resolving this question of photochemical control of vivianite redox chemistry is important for performing and interpreting experiments involving vivianite reactivity with contaminants, and potentially iron and phosphate cycling in the photic zone of aquatic systems. The present study was specifically designed to add¬ress this question. Pure synthetic vivianite samples were irradiated in aqueous suspensions with a Xe lamp at conditions mimicking the solar spectrum and compared to dark controls. Particles stirred in anoxic suspensions for up to 66 days showed no detectable oxidation irrespective of light exposure, according to colorimetric Fe2+/Fe3+ assays, micro X-ray diffraction, and Raman spectroscopy. In contrast, the same experiment performed using air-equilibrated suspensions showed systematic oxidation of up to ~80% mol% Fe(II) at 66 days, but again with no detectable light exposure effect. To test for UV reactivity, further experiments on vivianite powders under air versus N2 atmosphere were performed using a Hg lamp with a longpass filter. In contrast to oxidation in air where no effect of light was detected, after 24 hrs irradiation anoxically, 0.78% Fe was oxidized compared to dark controls, and after 13 days only an additional 0.3% Fe was oxidized. The band gap of pure vivianite was measured by the Tauc method to be 3.5 eV. Contrary to previous reports, solar light has minimal impact on the oxidation of pure vivianite, insignificant in particular when compared to its relatively fast oxidation by oxygen exposure. As such, light does not need to be excluded when running typical vivianite laboratory experiments. Long-term storage of natural vivianite in museums or private collections should continue protective measures given that a possible photocatalytic role of impurities cannot yet be ruled out. Nonetheless, at all depths in natural aquatic systems it appears that the primary abiotic control on the reactivity and half-life of vivianite particles should be the dissolved oxygen concentration, not light exposure.

Vivianite, photochemistry, oxidation↗

Associations between SARS-CoV-2 Infection or COVID-19 Vaccination and Human Milk Composition: A Multi-Omics Approach

Background: The risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via human milk-feeding is virtually nonexistent. Adverse effects of coronavirus disease 2019 (COVID-19) vaccination for lactating individuals are not different from the general population, and no evidence has been found that their infants exhibit adverse effects. Yet, there remains substantial hesitation among this population globally regarding the safety of these vaccines. Objectives: Herein, we aimed to determine if compositional changes in milk occur following SARS-CoV-2 infection or COVID-19 vaccination, including any evidence of vaccine components. Methods: An extensive multiomics approach was taken using a subset of milk samples obtained as part of our broad studies examining the effects on milk of SARS-CoV-2 infection and COVID-19 vaccination. Results: We found that compared with unvaccinated individuals, SARS-CoV-2 infection was associated with significant compositional differences in 67 proteins, 385 lipids, and 13 metabolites. In contrast, COVID-19 vaccination was not associated with any changes in lipids or metabolites, although it was associated with changes in 13 or fewer proteins. Compositional changes in milk differed by vaccine. Changes following vaccination were greatest after 1–6 h for the mRNA-based Moderna vaccine (8 changed proteins), 3 d for the mRNA-based Pfizer (4 changed proteins), and adenovirus-based Johnson and Johnson (13 changed proteins) vaccines. Proteins that changed after both natural infection and Johnson and Johnson vaccine were associated mainly with systemic inflammatory responses. In addition, no vaccine components were detected in any milk sample. Conclusions: Together, our data provide evidence of only minimal changes in milk composition because of COVID-19 vaccination, with much greater changes after natural SARS-CoV-2 infection.

60 APPLIED LIFE SCIENCES↗

Inhomogeneous Distribution and Coarsening of y″ Precipitates in a Ni-Based Superalloy and Their Effect on Creep

It has been reported that the addition of Nb or Ta in the high Ti/Al ratio alloys promotes the formation of y″ precipitates solely and greatly contributes to the elevated temperature strength and resistance to creep deformation. In this study, the y''-dominant INCONEL alloy 725 (IN725) variants (named M725-Nb/Ta) modified with a high level of Nb/Ta additions and high Ti/Al ratio was chosen as a model alloy for microstructural observation of y'' variants upon creep. Following the high temperature aging (HTA), y'' was found to be the main strengthening precipitate with no detectable y’ in both M725 alloys. After creep, the grip/gage sections of the crept M725-Nb/Ta exhibited preferential coarsening and inhomogeneous distribution of y''. That is, one or two of the variants were preferentially coarsened at the expense of another variant, and sandwich-like structures, comprising of cubic y′ precipitates with small y″ discs on each face, were formed. This variant selection behavior taking place in the grip section with no stress applied was different from the typical stress-induced variant selection in previous literature. However, the sample with prior high temperature exposure (700 °C for 500 hours) with varying y″ characteristics demonstrated a similar trend of creep when compared with those in the HTA sample, suggesting that the coarsening and the inhomogeneous distribution of y'' was not the determinant of creep life in bulk M725-Nb/Ta alloys.

Hung, Chang-Yu↗

Low Peripheral Blood Counts and Elevated Proinflammatory Cytokines Signal a Poor CD19 Chimeric Antigen Receptor T-cell Response in Acute Lymphoblastic Leukemia

CD19 chimeric antigen receptor T-cell (CAR-T) therapy has significantly improved outcomes for patients with relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL). However, approximately 20% of patients fail to achieve a complete remission (CR), and some develop severe, life-threatening toxicities. Understanding the biological mechanisms underlying both dysfunctional responses and severe toxicity is essential for optimizing patient management and improving therapeutic efficacy. This study aimed to (1) characterize cytokine profiles associated with dysfunctional responses and severe toxicity following CAR-T infusion, (2) examine the timing and trajectory of cytokine changes in relation to treatment outcomes, and evaluate potential strategies for mitigating toxicity and treatment failure. We conducted a comprehensive analysis of serum cytokine profiles in 86 adult and pediatric patients undergoing autologous CD19 CAR-T therapy for B-ALL. Patients were categorized into three groups: (1) Dysfunctional response—Patients who failed to achieve a minimal residual disease-negative CR (MRD-CR) by Day 63 or who experienced recurrence of CD19+ disease in the setting ongoing CAR-T cell detection before Day 63. (2) Functional response with severe cytokine release syndrome (CRS) and/or neurotoxicity (NTX)—Patients with best response of MRD-CR by Day 63 who experienced grade 3 or higher CRS or NTX. (3) Functional response without severe CRS or NTX—Patients with best response of MRD-CR by Day 63 who did not experience grade =3 CRS or NTX. Cytokine levels were measured during the first-week postinfusion and correlated with treatment efficacy, toxicity outcomes, complete blood counts, and CAR-T expansion dynamics. This analysis aimed to better understand how cytokine profiles relate to patient outcomes and immune responses in CAR-T therapy. Patients with dysfunctional response exhibited decreased neutrophils, platelets, and levels of granulocytic cytokines (suggestive of low bone marrow reserve) alongside elevated pro-inflammatory cytokines by Day 1. Functional response with severe toxicity patients showed a progressive rise in proinflammatory cytokines, reaching similar levels to dysfunctional response patients by Day 7. We observed that high cytokines at both the Day 1 and Day 7 time points were associated with poor survival. These findings remained significant when adjusting for high disease burden, a known predictor of severe inflammatory toxicity and lack of response. Early post-CAR-T infusion inflammation is associated with both dysfunctional response and severe toxicity—even after adjusting for disease burden. This suggests that inflammation, in addition to disease burden, plays a role in determining patient outcome. Therefore, strategies aimed at reducing the pro-inflammatory state prior to or early after CAR-T cell infusion may improve outcomes for R/R B-ALL patients.

Serum cytokines↗

Prophylactic treatment with PEGylated bovine IFNλ3 effectively bridges the gap in vaccine-induced immunity against FMD in cattle

Foot-and-mouth disease (FMD) is a vesicular disease of cloven-hoofed animals with devastating economic implications. The current FMD vaccine, routinely used in enzootic countries, requires at least 7 days to induce protection. However, FMD vaccination is typically not recommended for use in non-enzootic areas, underscoring the need to develop new fast-acting therapies for FMD control during outbreaks. Interferons (IFNs) are among the immune system’s first line of defense against viral infections. Bovine type III IFN delivered by a replication defective adenovirus (Ad) vector has effectively blocked FMD in cattle. However, the limited duration of protection—usually only 1–3 days post-treatment (dpt)—diminishes its utility as a field therapeutic. Here, we test whether polyethylene glycosylation (PEGylation) of recombinant bovine IFNλ3 (PEGboIFNλ3) can extend the duration of IFN-induced prevention of FMDV infection in both vaccinated and unvaccinated cattle. We treated groups of heifers with PEGboIFNλ3 alone or in combination with an adenovirus-based FMD O1Manisa vaccine (Adt-O1M) at either 3 or 5 days prior to challenge with homologous wild type FMDV. We found that pre-treatment with PEGboIFNλ3 was highly effective at preventing clinical FMD when administered at either time point, with or without co-administration of Adt-O1M vaccine. PEGboIFNλ3 protein was detectable systemically for >10 days and antiviral activity for 4 days following administration. Furthermore, in combination with Adt-O1M vaccine, we observed a strong induction of FMDV-specific IFNγ+ T cell response, demonstrating its adjuvanticity when co-administered with a vaccine. Our results demonstrate the promise of this modified IFN as a pre-exposure prophylactic therapy for use in emergency outbreak scenarios.

biotherapeutics↗

Avian Activity Classification Using Recurrent Networks to Fuse Videos with Metadata on Imbalanced Datasets

Activity classification plays a crucial role in various real-life scenarios involving both humans and animals. There is an increasing need for precise activity classification focused on avian-solar interactions, as the usage of solar energy facilities, such as photovoltaic array power stations, has been observed to impact bird species richness, behavior, and activity. However, there has been no work to develop an automated system to monitor and classify these avian-solar interactions. All current methods rely on human observers, which is time and human resources costly and subject to errors related to searcher efficiency. With the recent success of Deep Learning models in activity classification problems, this paper develops a recurrent neural network-based model to automatically classify six avian activities around solar energy facilities. Our proposed model integrates critical feature engineering metadata with video frame data, enabling improved learning and more accurate activity classification. Furthermore, we address the challenge of data imbalance during training and demonstrate the efficacy of our model in detecting and classifying different activities within video tracks. Additionally, we analyze the saliency/backpropagation map of the trained proposed model and validate its decision-making rationale.

Avian activity classification; bidirectional LSTM;↗

Efficacy of commercial recombinant HVT vaccines against a North American clade 2.3.4.4b H5N1 highly pathogenic avian influenza virus in chickens

The outbreak of clade 2.3.4.4b H5 highly pathogenic avian influenza (HPAI) in North America that started in 2021 has increased interest in applying vaccination as a strategy to help control and prevent the disease in poultry. Two commercially available vaccines based on the recombinant herpes virus of turkeys (rHVT) vector were tested against a recent North American clade 2.3.4.4b H5 HPAI virus isolate: A/turkey/Indiana/22-003707-003/2022 H5N1 in specific pathogen free white leghorn (WL) chickens and commercial broiler chickens. One rHVT-H5 vaccine encodes a hemagglutinin (HA) gene designed by the computationally optimized broadly reactive antigen method (COBRA-HVT vaccine). The other encodes an HA gene of a clade 2.2 virus (2.2-HVT vaccine). There was 100% survival of both chicken types COBRA-HVT vaccinated groups and in the 2.2-HVT vaccinated groups there was 94.8% and 90% survival of the WL and broilers respectively. Compared to the 2.2-HVT vaccinated groups, WL in the COBRA-HVT vaccinated group shed significantly lower mean viral titers by the cloacal route and broilers shed significantly lower titers by the oropharyngeal route than broilers. Virus titers detected in oral and cloacal swabs were otherwise similar among both vaccine groups and chicken types. To assess antibody-based tests to identify birds that have been infected after vaccination (DIVA-VI), sera collected after the challenge were tested with enzyme-linked lectin assay-neuraminidase inhibition (ELLA-NI) for N1 neuraminidase antibody detection and by commercial ELISA for detection of antibodies to the NP protein. As early as 7 days post challenge (DPC) 100% of the chickens were positive by ELLA-NI. ELISA was less sensitive with a maximum of 75% positive at 10DPC in broilers vaccinated with 2.2-HVT. Both vaccines provided protection from challenge to both types of chickens and ELLA-NI was sensitive at identifying antibodies to the challenge virus therefore should be evaluated further for DIVA-VI.

60 APPLIED LIFE SCIENCES↗

Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network

This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.

15 GEOTHERMAL ENERGY↗

Subventricular Accumulation of Cu in the Aging Mouse Brain Does Not Associate with Anticipated Increases in Markers of Oxidative Stress

Natural aging is associated with mild memory loss and cognitive decline, and age is the greatest risk factor for neurodegenerative diseases, such as Alzheimer’s disease. There is substantial evidence that oxidative stress is a major contributor to both natural aging and neurodegenerative disease, and coincidently, levels of redox active metals such as Fe and Cu are known to be elevated later in life. Recently, a pronounced age-related increase in Cu content has been reported to occur in mice and rats around a vital regulatory brain region, the subventricular zone of lateral ventricles. In our study herein, we have characterized lateral ventricle Cu content in a unique murine model of accelerated aging, senescence accelerated mouse-prone 8 (SAMP8) mice. Our results confirm an age-related increase in ventricle Cu content, consistent with the studies by others in wild-type mice and rats. Specifically, we observed Cu content to increase over the time frame 1 to 5 months and 5 to 9 months, but interestingly, no significant increase occurred between 9 and 12 months (although brain Cu content at 12 months was significantly elevated relative to 1 and 5 month-old animals). Despite the magnitude of Cu increase observed within the cells that comprise the subventricular zone of lateral ventricles (average 3 mM Cu, with isolated subcellular concentrations of 17 mM), we did not detect spectroscopic markers of thiol oxidation, protein aggregation, or lipid oxidation. The lack of evidence for oxidative stress in ex vivo animal tissue is in contrast to in vitro studies demonstrating that thiol, protein, and lipid oxidation is pronounced at these Cu concentrations. We suggest that our findings most likely indicate that the Cu ions in this brain region are sequestered in an unreactive form, possibly extended chains of Cu-thiolate complexes, which do not readily redox cycle in the aqueous cytosol. In conclusion, these results also appear to partially challenge the long-held view that age-related increases in brain metal content drive oxidative stress as we did not observe a concomitant association between age-related Cu increase and markers of oxidative stress, nor did we observe a net increase in Cu content between mice aged 9 and 12 months.

X-ray fluorescence↗

Fungal diversity and function in metagenomes sequenced from extreme environments

Fungi are increasingly recognized as key players in various extreme environments. Here we present an analysis of publicly-sourced metagenomes from global extreme environments, focusing on fungal taxonomy and function. The majority of 855 selected metagenomes contained scaffolds assigned to fungi. Relative abundance of fungi was as high as 10% of protein-coding genes with taxonomic annotation, with up to 289 fungal genera per sample. Despite taxonomic clustering by environment, fungal communities were more dissimilar than archaeal and bacterial communities, both for within- and between-environment comparisons. Relatively abundant fungal classes in extreme environments included Dothideomycetes, Eurotiomycetes, Leotiomycetes, Pezizomycetes, Saccharomycetes, and Sordariomycetes. Broad generalists and prolific aerial spore formers were the most relatively abundant fungal genera detected in most of the extreme environments, bringing up the question of whether they are actively growing in those environments or just surviving as spores. More specialized fungi were common in some environments, such as zoosporic taxa in cryosphere water and hot springs. Relative abundances of genes involved in adaptation to general, thermal, oxidative, and osmotic stress were greatest in soda lake, acid mine drainage, and cryosphere water samples.

60 APPLIED LIFE SCIENCES↗