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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Circulating SARS-CoV-2 + megakaryocytes are associated with severe viral infection in COVID-19

Several independent lines of evidence suggest that megakaryocytes are dysfunctional in severe COVID-19. Herein, we characterized peripheral circulating megakaryocytes in a large cohort of inpatients with COVID-19 and correlated the subpopulation frequencies with clinical outcomes. Using peripheral blood, we show that megakaryocytes are increased in the systemic circulation in COVID-19, and we identify and validate S100A8/A9 as a defining marker of megakaryocyte dysfunction. We further reveal a subpopulation of S100A8/A9 + megakaryocytes that contain severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protein and RNA. Using flow cytometry of peripheral blood and in vitro studies on SARS-CoV-2–infected primary human megakaryocytes, we demonstrate that megakaryocytes can transfer viral antigens to emerging platelets. Mechanistically, we show that SARS-CoV-2–containing megakaryocytes are nuclear factor κB (NF-κB)-activated, via p65 and p52; express the NF-κB–mediated cytokines interleukin-6 (IL-6) and IL-1β; and display high surface expression of Toll-like receptor 2 (TLR2) and TLR4, canonical drivers of NF-κB. In a cohort of 218 inpatients with COVID-19, we correlate frequencies of megakaryocyte subpopulations with clinical outcomes and show that SARS-CoV-2–containing megakaryocytes are a strong risk factor for mortality and multiorgan injury, including respiratory failure, mechanical ventilation, acute kidney injury, thrombotic events, and intensive care unit admission. Furthermore, we show that SARS-CoV-2 + megakaryocytes are present in lung and brain autopsy tissues from deceased donors who had COVID-19. To our knowledge, this study offers the first evidence implicating SARS-CoV-2 + peripheral megakaryocytes in severe disease and suggests that circulating megakaryocytes warrant investigation in inflammatory disorders beyond COVID-19.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Age over sex: evaluating gut microbiota differences in healthy Chinese populations

Age and gender have been recognized as two pivotal covariates affecting the composition of the gut microbiota. However, their mediated variations in microbiota seem to be inconsistent across different countries and races. In this study, 613 individuals, whom we referred to as the “healthy” population, were selected from 1,018 volunteers through rigorous selection using 16S rRNA sequencing. Three enterotypes were identified, namely, Escherichia–Shigella , mixture ( Bacteroides and Faecalibacterium ), and Prevotella . Moreover, 11 covariates that explain the differences in microbiota were determined, with age being the predominant factor. Furthermore, age-related differences in alpha diversity, beta diversity, and core genera were observed in our cohort. Remarkably, after adjusting for 10 covariates other than age, abundant genera that differed between age groups were demonstrated. In contrast, minimal differences in alpha diversity, beta diversity, and differentially abundant genera were observed between male and female individuals. Furthermore, we also demonstrated the age trajectories of several well-known beneficial genera, lipopolysaccharide (LPS)-producing genera, and short-chain fatty acids (SCFAs)-producing genera. Overall, our study further elucidated the effects mediated by age and gender on microbiota differences, which are of significant importance for a comprehensive understanding of the gut microbiome spectrum in healthy individuals.

Wu, Jiacheng↗
DOE OSTI2023

Pan-cancer evaluation of clinical value of mitotic network activity index (MNAI) and its predictive value for immunotherapy

Increased mitotic activity is associated with the genesis and aggressiveness of many cancers. To assess the clinical value of mitotic activity as prognostic biomarker, we performed a pan-cancer study on the mitotic network activity index (MNAI) constructed based on 54-gene mitotic apparatus network. Our pan-cancer assessment on TCGA (33 tumor types, 10,061 patients) and validation on other publicly available cohorts (23 tumor types, 9,209 patients) confirmed the significant association of MNAI with overall survival, progression-free survival, and other prognostic endpoints in multiple cancer types, including lower-grade gliomas (LGG), breast invasive carcinoma (BRCA), as well as many others. We also showed significant association between MNAI and genetic instability, which provides a biological explanation of its prognostic impact at pan-cancer landscape. Our association analysis revealed that patients with high MNAI benefitted more from anti-PD-1 and Anti-CTLA-4 treatment. In addition, we demonstrated that multimodal integration of MNAI and the AI-empowered Cellular Morphometric Subtypes (CMS) significantly improved the predictive power of prognosis compared to using MNAI and CMS alone. Our results suggest that MNAI can be used as a potential prognostic biomarker for different tumor types toward different clinical endpoints, and multimodal integration of MNAI and CMS exceeds individual biomarker for precision prognosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Genetic background influences the effect of thirdhand smoke exposure on anxiety and memory in Collaborative Cross mice

Growing evidence indicates that thirdhand smoke (THS) exposure induces many adverse health effects. However, it is unclear how THS exposure affects behavior and how host genetic background modulates phenotypic changes. Here we used the Collaborative Cross (CC) mouse population-based model to assess behavioral alterations immediately after THS exposure from 4 to 9 weeks of age. We first measured anxiety-like behavior in six strains using light/dark box combined with a custom multivariate mouse tracking system. We developed an anxiety risk scoring system based on anxiety-related traits and then evaluated the THS impact on them. THS exposure significantly decreased anxiety risk in CC019 ( P = 0.002) and CC051 ( P = 0.009), but increased anxiety risk in CC036 ( P < 0.001), while the other three strains did not show significant changes in anxiety-related traits. Such differences were driven by female mice for the six measures of anxiety-like behavior. Memory potential was measured in the same cohort of mice using the passive avoidance assay. Both THS-exposed male and female CC019 mice displayed significant memory loss compared to controls while no significant changes were found in the other five strains. This study provides strong evidence that THS exposure leads to strain-dependent changes in anxiety-like behavior and memory, suggesting that host genetic variations play a critical role in individual susceptibility to THS-induced effects.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Congenital Malformations and Perinatal Deaths Among the Children of Atomic Bomb Survivors: A Reappraisal

From 1948 to 1954, the Atomic Bomb Casualty Commission conducted a study of pregnancy outcomes among births to atomic bomb survivors (Hiroshima and Nagasaki, Japan) who had received radiation doses ranging from 0 Gy to near-lethal levels. Past reports (1956, 1981, and 1990) on the cohort did not identify significant associations of radiation exposure with untoward pregnancy outcomes, such as major congenital malformations, stillbirths, or neonatal deaths, individually or in aggregate. We reexamined the risk of major congenital malformations and perinatal deaths in the children of atomic bomb survivors (n = 71,603) using fully reconstructed data to minimize the potential for bias, using refined estimates of the gonadal dose from Dosimetry System 2002 and refined analytical methods for characterizing dose-response relationships. The analyses showed that parental exposure to radiation was associated with increased risk of major congenital malformations and perinatal death, but the estimates were imprecise for direct radiation effects, and most were not statistically significant. Nonetheless, the uniformly positive estimates for untoward pregnancy outcomes among children of both maternal and paternal survivors are useful for risk assessment purposes, although extending them to populations other than the atomic bomb survivors comes with uncertainty as to generalizability.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Step-patterned survivorship curves: Mortality and loss of equilibrium responses to high temperature and food restriction in juvenile rainbow trout ( Oncorhynchus mykiss )

While survivorship curves typically exhibit smooth declines over time, step-patterned curves can occur with multiple stressors within a life stage. To explore this process, we examined the effects of heat (24°C) and food restriction on juvenile rainbow trout (Oncorhynchus mykiss Walbaum) in challenge experiments. We observed step-patterned survivorship curves determined by mortality and loss of equilibrium (LOE) endpoints. To examine the cause of heterogeneity in the stress responses from early to late mortality and LOE, we measured indices of energetic reserves. The step transition in the survivorship curves, the peak mortality rates, and start of when individuals reached a critical energetic threshold (14% dry mass; 4.0 kJ∙g -1 energy) all occurred at around days 10–15 of the challenge. The coherence in these temporal patterns suggest heterogeneity in the cohort stress responses, in which an early subgroup died from heat stress and a late subgroup died from starvation. Thus, their endpoint sensitivities resulted in step-patterned survivorship curves. We discuss the implications of the study for understanding effects of multiple stressors on population heterogeneity and note the possible significance of stress response selection under climate change in which heat stress and food limitations occur in concert.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Associations between Frequency of Culinary Herb Use and Gut Microbiota

While evidence suggests that culinary herbs have the potential to modulate gut microbiota, much of the current research investigating the interactions between diet and the human gut microbiome either largely excludes culinary herbs or does not assess use in standard culinary settings. As such, the primary objective of this study was to evaluate how the frequency of culinary herb use is related to microbiome diversity and the abundance of certain taxa, measured at the phylum level. In this secondary data analysis of the INCLD Health cohort, we examined survey responses assessing frequency of culinary herb use and microbiome analysis of collected stool samples. We did not observe any associations between frequency of culinary herb use and Shannon Index, a measure of alpha diversity. Regarding the abundance of certain taxa, the frequency of use of polyphenol-rich herbs and herbs with certain quantities of antibacterial compounds was positively associated with Firmicutes abundance, and negatively associated with Proteobacteria abundance. Additionally, the total number of herbs used with high frequency, defined as over three times per week, was also positively associated with Firmicutes abundance, independent of adjustments, and negatively associated with Proteobacteria abundance, after adjusting for dietary factors. Frequency of culinary herb use was not associated with Bacteroidota or Actinobacteria abundance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Cross talk between RNA N6‐methyladenosine methyltransferase‐like 3 and miR‐186 regulates hepatoblastoma progression through Wnt/β‐catenin signalling pathway

Abstract Objectives N6‐methyladenosine (m6A) is a ubiquitous epigenetic RNA modification that plays a pivotal role in tumour development and metastasis. In this study, we aimed to investigate the expression profiling, clinical significance, biological function and the regulation of m6A‐related genes in hepatoblastoma (HB). Materials and Methods The mRNA and protein expression levels of m6A‐related genes were analysed using Gene Expression Omnibus (GEO) and tissue microarray (TMA) cohort. Kaplan‐Meier analysis was performed to evaluate the prognostic value of m6A‐related genes in HB. Knockdown of m6A‐related genes was conducted to analyse its function on cell proliferation, migration and invasion. Furthermore, bioinformatics analysis and experimental verification were used to explore the potential molecular mechanism and signalling pathway. Results We found that most m6A‐related genes were significantly upregulated in HB tumour tissues. High levels of methyltransferase‐like 3 (METTL3, P = .013), YTHDF2 ( P = .037) and FTO ( P = .032) indicated poor clinical outcomes, and the upregulation of METTL3 was an independent prognostic factor in HB patients. Functional assays showed that knockdown of METTL3 could dramatically suppress the proliferation, migration and invasion of HB cells. In addition, METTL3 was identified to be a direct target of microRNA‐186 (miR‐186). Consistently, miR‐186 was low expressed in HB tumour tissues. Moreover, overexpression of miR‐186 significantly inhibited cell aggressive phenotype both in vitro and in vivo, while the inhibitory effect could be reversed by METTL3 overexpression. Mechanism study indicated that miR‐186/METTL3 axis contributed to the progression of HB via the Wnt/β‐catenin signalling pathway. Conclusions M6A‐related genes were frequently dysregulated in HB. miR‐186/METTL3/Wnt/β‐catenin axis might serve as novel therapeutic targets and prognostic biomarkers in HB.

Cui, Xichun↗
DOE OSTI2020

Deep neural network improves the estimation of polygenic risk scores for breast cancer

Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. Here, we compared a series of computational models for estimation of breast cancer PRS. A deep neural network (DNN) was found to outperform alternative machine learning techniques and established statistical algorithms, including BLUP, BayesA, and LDpred. In the test cohort with 50% prevalence, the Area Under the receiver operating characteristic Curve (AUC) were 67.4% for DNN, 64.2% for BLUP, 64.5% for BayesA, and 62.4% for LDpred. BLUP, BayesA, and LPpred all generated PRS that followed a normal distribution in the case population. However, the PRS generated by DNN in the case population followed a bimodal distribution composed of two normal distributions with distinctly different means. This suggests that DNN was able to separate the case population into a high-genetic-risk case subpopulation with an average PRS significantly higher than the control population and a normal-genetic-risk case subpopulation with an average PRS similar to the control population. This allowed DNN to achieve 18.8% recall at 90% precision in the test cohort with 50% prevalence, which can be extrapolated to 65.4% recall at 20% precision in a general population with 12% prevalence. Interpretation of the DNN model identified salient variants that were assigned insignificant p values by association studies, but were important for DNN prediction. These variants may be associated with the phenotype through nonlinear relationships.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Chronic obstructive pulmonary disease among former United States Department of Energy workers: comorbidities and lung function changes

Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality in the United States and is frequently associated with multiple comorbidities which lead to poor COPD outcomes in the general population. However, little is known regarding COPD comorbidities in occupational cohorts whose exposure experiences could result in differences in comorbidities compared to the general population. These differences may also be important for assessing COPD outcomes such as lung function changes or decline. Therefore, the objectives of this study were to: (1) identify and describe clusters of COPD comorbidities among Department of Energy (DOE) former workers; (2) assess if the attributes of the identified clusters differ from those identified among the general population based on the published literature, and (3) identify predictors of lung function changes and decline among DOE former workers.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Predictive models of long COVID

Background: The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future. Methods: We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models — logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the ‘long COVID’ label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741). Findings: LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75. Interpretation: ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Statistically Driven Metabolite and Lipid Profiling of Patients from the Undiagnosed Diseases Network

Advancements in molecular separations coupled with mass spectrometry have enabled large-scale metabolome analyses for clinical cohorts. A population of interest for metabolome profiling are patients with rare disease for which abnormal metabolic signatures may yield clues into the genetic bases, as well as mechanistic drivers of the disease and possible treatment options. We undertook the metabolome profiling of a large cohort of patients with mysterious conditions characterized through the Un-diagnosed Diseases Network (UDN). Due to the size and enrollment procedures, collection of the metabolomes for UDN pa-tients took place over three years. We describe the study design to adjust for measurements collected over a long time-scale and how this enabled statistical analyses to summarize the metabolome of individual patients. We demonstrate the removal of time-based batch effects, overall statistical characteristics of the UDN population, and two case-studies of interest that demonstrate the utility of metabolome profiling for rare diseases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

Do Astronauts Havbe a Higher Rate of Orthopedic Shoulder Conditions Than a Cohort of Working Professionals

Occupational surveillance of astronaut shoulder injuries began with operational concerns at the Neutral Buoyancy Laboratory (NBL) during Extra Vehicular Activity (EVA) training. Orthopedic shoulder injury and surgery rates were calculated [1], but classifying the rates as normal, high or low was highly dependent on the comparison group. Thus, the purpose of this study was to identify a population of working professionals and compare orthopedic shoulder consultation and surgery rates.

Laughlin, M. S.↗
DOE OSTI2021

Normal Tissue Injury Induced by Photon and Proton Therapies: Gaps and Opportunities

Despite technological advances in radiation therapy (RT) and cancer treatment, patients still experience adverse effects. Proton therapy (PT) has emerged as a valuable RT modality that can improve treatment outcomes. Normal tissue injury is an important determinant of the outcome; therefore, for this review, we analyzed 2 databases: (1) clinical trials registered with ClinicalTrials.gov and (2) the literature on PT in PubMed, which shows a steady increase in the number of publications. Most studies in PT registered with ClinicalTrials.gov with results available are nonrandomized early phase studies with a relatively small number of patients enrolled. From the larger database of nonrandomized trials, we listed adverse events in specific organs/sites among patients with cancer who are treated with photons and protons to identify critical issues. The present data demonstrate dosimetric advantages of PT with favorable toxicity profiles and form the basis for comparative randomized prospective trials. A comparative analysis of 3 recently completed randomized trials for normal tissue toxicities suggests that for early stage non-small cell lung cancer, no meaningful comparison could be made between stereotactic body RT and stereotactic body PT due to low accrual (NCT01511081). In addition, for locally advanced non-small cell lung cancer, a comparison of intensity modulated RT with passive scattering PT (now largely replaced by spot-scanned intensity modulated PT), PT did not provide any benefit in normal tissue toxicity or locoregional failure over photon therapy. Finally, for locally advanced esophageal cancer, proton beam therapy provided a lower total toxicity burden but did not improve progression-free survival and quality of life (NCT01512589). The purpose of this review is to inform the limitations of current trials looking at protons and photons, considering that advances in technology, physics, and biology are a continuum, and to advocate for future trials geared toward accurate precision RT that need to be viewed as an iterative process in a defined path toward delivering optimal radiation treatment. A foundational understanding of the radiobiologic differences between protons and photons in tumor and normal tissue responses is fundamental to, and necessary for, determining the suitability of a given type of biologically optimized RT to a patient or cohort.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2024

Risk of Bone Fracture due to Spaceflight-induced Changes to Bone

The Human Research Program (HRP) is taking a biomechanical approach to assessing subsequent fracture risk in active astronauts as a consequence of spaceflight exposure. Triennial testing of active and retired astronauts continues as Space Medicine monitors for a premature diagnosis of primary osteoporosis, which is associated with age-related bone loss and skeletal fragility. This updated 2023 Fracture Evidence Report has expanded the description of skeletal changes to capture the full effects of spaceflight on bone: • Recent analysis of fractures from health records of the full astronaut cohort, suggests an increased incidence rate of hip and spine fractures in astronauts following longer spaceflight duration flights compared to incident rates found in shorter duration flights. • Routine preflight-to-postflight surveillance by DXA (dual-energy x-ray absorptiometry) does not provide the full detection of loss and recovery in the long-duration (LD) astronaut nor the full recovery of hip trabecular bone. • The inclusion of hip quantitative computed tomography (QCT) in flight studies delineates effects of spaceflight, of countermeasures, and of post-flight recovery on cortical and trabecular bone parameters—some of which are verified predictors of hip fracture in the aged. • QCT detects and compares the distinct countermeasure effects of the pharmaceutical alendronate and of resistive exercise (on the Advanced Resistive Exercise Device, ARED) in specific cortical and trabecular bone sub-regions during spaceflight. • A published comparison of QCT-determined loss rates of hip trabecular bone in LD astronauts compared to terrestrial cohorts suggest that accelerated loss rates in trabecular volumetric BMD (vBMD) during spaceflight might be analogous to skeletal effects of accelerated loss rates in females due to menopause, potentially leading to disruptions in trabecular microarchitecture. • A dataset of finite element (FE) estimates of hip bone strength in aging terrestrial cohorts (spanning astronaut age-range) provides comparative context for changes in the FE of hip bone strength in LD astronauts, including comparison (force unit of newton) to percentiles (50th, 75th, and 100th) of sex-matched aged humans with hip fractures. • Risk of fracture, due to the mechanical overloading of bones, is being updated with IMPACT, the next-generation tool suite for probabilistic risk assessment (PRA) for exploration missions being created by the Exploration and Medical Capability Element (ExMC) at NASA. IMPACT is currently in development and will not be included in this 2024 update. The risk for fracture necessitates understanding the relationship between applied loads to bone and the biomechanical competence of bone. The Risk for Early Onset Osteoporosis focuses on the weakened condition of bone (including development of new technologies, measurements of novel skeletal attributes, translation of multiple measures to an index of bone fragility, and interpretations of data used to reflect a weakened bone), while the Risk for Fracture assesses factors that influence the probability an astronaut would encounter applied loads exceeding the biomechanical competence of bones, resulting in fracture. This Evidence Report combines the research gaps and tasks associated with both risks.

Fracture↗
DOE OSTI2023

Using iterative random forest to find geospatial environmental and Sociodemographic predictors of suicide attempts

Despite a recent global decrease in suicide rates, death by suicide has increased in the United States. It is therefore imperative to identify the risk factors associated with suicide attempts to combat this growing epidemic. In this study, we aim to identify potential risk factors of suicide attempt using geospatial features in an Artificial intelligence framework. We use iterative Random Forest, an explainable artificial intelligence method, to predict suicide attempts using data from the Million Veteran Program. This cohort incorporated 405,540 patients with 391,409 controls and 14,131 attempts. Our predictive model incorporates multiple climatic features at ZIP-code-level geospatial resolution. We additionally consider demographic features from the American Community Survey as well as the number of firearms and alcohol vendors per 10,000 people to assess the contributions of proximal environment, access to means, and restraint decrease to suicide attempts. In total 1,784 features were included in the predictive model. Our results show that geographic areas with higher concentrations of married males living with spouses are predictive of lower rates of suicide attempts, whereas geographic areas where males are more likely to live alone and to rent housing are predictive of higher rates of suicide attempts. We also identified climatic features that were associated with suicide attempt risk by age group. Additionally, we observed that firearms and alcohol vendors were associated with increased risk for suicide attempts irrespective of the age group examined, but that their effects were small in comparison to the top features. Taken together, our findings highlight the importance of social determinants and environmental factors in understanding suicide risk among veterans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The Dutch–Belgian Registry of Stereotactic Body Radiation Therapy for Liver Metastases: Clinical Outcomes of 515 Patients and 668 Metastases

Although various studies have reported that stereotactic body radiation therapy (SBRT) for liver metastases has high local control rates and relatively low toxicity, most series included a small number of patients. We aimed to validate these outcomes in a large multi-institution patient cohort treated in accordance with a common protocol.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Systemic immunological responses are dependent on sex and ovarian hormone presence following acute inhaled woodsmoke exposure

Background: Rural regions of the western United States have experienced a noticeable surge in both the frequency and severity of acute wildfire events, which brings significant challenges to both public safety and environmental conservation efforts, with impacts felt globally. Identifying factors contributing to immune dysfunction, including endocrinological phenotypes, is essential to understanding how hormones may influence toxicological susceptibility. Methods: This exploratory study utilized male and female C57BL/6 mice as in vivo models to investigate distinct responses to acute woodsmoke (WS) exposure with a focus on sex-based differences. In a second set of investigations, two groups were established within the female mouse cohort. In one group, mice experienced ovariectomy (OVX) to simulate an ovarian hormone-deficient state similar to surgical menopause, while the other group received Sham surgery as controls, to investigate the mechanistic role of ovarian hormone presence in driving immune dysregulation following acute WS exposure. Each experimental cohort followed a consecutive 2-day protocol with daily 4-h exposure intervals under two conditions: control HEPA-filtered air (FA) and acute WS to simulate an acute wildfire episode. Results: Metals analysis of WS particulate matter (PM) revealed significantly increased levels of 63 Cu, 182 W, 208 Pb, and 238 U, compared to filtered air (FA) controls, providing insights into the specific metal components most impacted by the changing dynamics of wildfire occurrences in the region. Male and female mice exhibited diverse patterns in lung mRNA cytokine expression following WS exposure, with males showing downregulation and females displaying upregulation, notably for IL-1β, TNF-α, CXCL-1, CCL-5, TGF-β, and IL-6. After acute WS exposure, there were notable differences in the responses of macrophages, neutrophils, and bronchoalveolar lavage (BAL) cytokines IL-10, IL-6, IL-1β, and TNF-α. Significant diverse alterations were observed in BAL cytokines, specifically IL-1β, IL-10, IL-6, and TNF-α, as well as in the populations of immune cells, such as macrophages and polymorphonuclear leukocytes, in both Sham and OVX mice, following acute WS exposure. These findings elucidated the profound influence of hormonal changes on inflammatory outcomes, delineating substantial sex-related differences in immune activation and revealing altered immune responses in OVX mice due to ovarian hormone deficiency. In addition, the flow cytometry analysis highlighted the complex interaction between OVX surgery, acute WS exposure, and their collective impact on immune cell populations within the hematopoietic bone marrow niche. Conclusions: In summary, both male and female mice, alongside females subjected to OVX and those who had sham surgery, exhibit significant variations in the expression of proinflammatory cytokines, chemokines, lung mRNA gene expression, and related functional networks linked to signaling pathways. These differences potentially act as mediators of sex-specific and hormonal influences in the systemic inflammatory response to acute WS exposure during a wildfire event. Understanding the regulatory roles of genes expressed differentially under environmental stressors holds considerable implications, aiding in identifying sex-specific therapeutic targets for addressing acute lung inflammation and injury.

59 BASIC BIOLOGICAL SCIENCES↗