Occupational cohorts are important to understanding the unique exposures of a workforce. The individuals selected by the National Aeronautics and Space Administration (NASA) to be astronauts experience occupational exposures unlike any other. To better understand the short- and long-term health effects of spaceflight, health and exposure data are collected on this cohort through clinical and other surveillance settings. This cohort is composed of the 360 astronauts who have been selected by NASA from the first selection class in 1959 to the most recent class of 2022. Selection of crewmembers is based on specific skills, education, military experience and fitness for flight. Due to the stringent and specific selection criteria, this occupational cohort encompasses a population that is more homogeneous than other groups. However, with the evolution of selection criteria along with changes to health screening and data collection processes, each selection class has a varying baseline health status. Data on a variety of health outcomes and risk factors have been collected along with occupational, physiological and exposure data, demographic and socioeconomic information and exposures that occurred prior to selection. Data have been used for both research activities, such as studies addressing Spaceflight Associated Neuro-ocular Syndrome and venous thromboembolism, and occupational surveillance activities like monitoring cardiovascular health preflight, in-flight and postflight. Characterisation of these factors helps not only with current monitoring but also informs future risk reduction decisions for exploration missions. As NASA plans missions to the Moon and Mars, the evidence base for this cohort will continue to grow through annual and mission-related data collection of current, future and retired crewmembers. Data for this cohort will continue to be collected as long as NASA continues to fly humans in space. As more data is collected, future research and surveillance activities will continue to be developed both internally and externally. One area that we aim to use this cohort is to compare with other cohorts to measure the risk of astronaut training and spaceflight, as some previous studies have done in the past.
NASA's rigorous medical selection has successfully limited in-flight medical emergencies throughout six decades of human spaceflight, but its effectiveness in identifying individuals with exceptional long-term survival remains unquantified. We estimated age-specific mortality rates based on 299 male US astronauts selected 1959-2021, using mortality data through 2022 (9602 person-years, 69 deaths). We restricted analyses to male astronauts due to insufficient follow-up time and observed mortality among female astronauts, who were first selected in 1978 and remain relatively young. We estimated astronaut hazards across the lifespan by combining rates from a Poisson regression model (for natural-cause mortality) with calculated empirical rates for external causes. These mortality rates were used to construct life tables, from which we derived life expectancy estimates and compared them to 2022 US general population values. Astronauts demonstrated substantial survival advantages at all ages, with life expectancy exceeding the general population by approximately 5 to 7 years between ages 30-70. At age 50, astronauts had a life expectancy of 36.7 years versus 29.1 years for the general population (a difference of 7.6 years). These findings quantify selection effectiveness as a countermeasure while highlighting fundamental epistemological limitations in using general population comparisons to assess spaceflight health risks.
Crewmembers on long-duration spaceflight missions are at risk of developing mild to moderate optic disc edema and ventricular volume expansion. The effect of repeat exposures on ocular and brain tissues is unknown and needs to be better understood for astronauts flying multiple missions. To evaluate whether a second exposure to spaceflight or a spaceflight analog is associated with larger changes in optic disc edema or brain ventricular volume expansion. Peripapillary total retinal thickness (TRT) extending from the Bruch membrane opening to 250 µm was quantified using optical coherence tomography imaging before and during spaceflight or the spaceflight analog head-down tilt bed rest (HDTBR). Magnetic resonance imaging was performed before and after spaceflight or HDTBR to quantify changes in brain volumetrics. Included were astronauts and participants in HDTBR from the International Space Station or German Aerospace Center :envihab facility. Study data were analyzed from November to December 2025. Two spaceflight missions of approximately 6 months or 2 HDTBR campaigns of 30 to 60 days in duration. The change in TRT (∆TRT) from preflight/pre-HDTBR to approximately 30 days before return to Earth or 30 days into HDTBR and the change in lateral ventricular volume (∆LVV) from preexposure to postexposure. Data were analyzed to determine if repeat exposure to spaceflight or HDTBR augmented the magnitude of change from the first exposure to the second. This study included a total of 7 astronauts (mean [SD] age, 43 [5] years; 5 male [71%]) and 5 participants in HDTBR (mean [SD] age, 35 [9] years; 3 male [60%]). ΔTRT was not different between spaceflight missions (mean difference, -5.6 µm; 95% CI, -15 to 3.7 µm; P = .23) or between HDTBR campaigns (mean difference, 3.1 µm; 95% CI, -3.3 to 9.5 µm; P = .33). ΔLVV was not different between spaceflight missions (mean difference, 0.1 mL; 95% CI, -0.9 to 1.1 mL; P = .78). The 3 participants in HDTBR with magnetic resonance imaging data presented with a similar ΔLVV after each campaign (0.4 vs 0.1, 1.1 vs 0.4, and 0.9 vs -0.2 mL, respectively). Findings of this case series show that a single repeat exposure to HDTBR or spaceflight did not appear to be associated with an increase in the magnitude of change in ocular or brain structures. Whether these exposures are additive in causing increased long-term functional changes remains unknown. These findings may be used by the space medicine community to guide the prediction of changes that might occur in those who undertake multiple spaceflight missions.
Bone loss occurs in astronauts during prolonged spaceflight, thus indicating the sensitivity of skeletal homeostasis to altered gravitational environments. Previous studies have shown that microgravity affects osteoclast differentiation and bone resorption, which suggests that osteoclasts possess mechanisms to sense and respond to gravity-generated mechanical forces. For testing of the related mechanisms, hypergravity can be experimentally reproduced with use of a centrifuge. In the present study, osteoclasts derived from mouse bone marrow were subjected to hypergravity under three conditions: 30G exposure using a non-CO2 centrifuge system, and short- or long-term exposure to 3G or 5G using an incubator-compatible centrifuge system. Cytoskeletal organization and resorptive function were assessed using TRAP (tartrate-resistant acid phosphatase) staining, F-actin visualization, and dentin pit assays. In addition, phosphoproteomic analysis was performed after short-term exposure to 5G hypergravity. Hypergravity exposure for as brief as 30 minutes compromised F-actin ring integrity, reduced fluorescence intensity, and promoted nuclear repositioning toward actin rings, whereas tubulin and vinculin localization remained unchanged, and the structural alterations corresponded to attenuated resorption pit formation. Quantitative phosphoproteomic profiling revealed coordinated hypergravity-dependent changes in phosphorylation across multiple cellular modules, including cytoskeletal organization, membrane trafficking, intracellular signaling, and nuclear regulatory pathways. Together, these results indicate that osteoclasts are sensitive to gravity-generated mechanical loading, with hypergravity rapidly modifying F-actin-associated cytoskeleton properties and reprogramming phosphorylation-dependent signaling networks, ultimately attenuating bone-resorptive activity. These findings provide mechanistic insight into how osteoclasts respond to altered gravitational loading conditions and have implications for skeletal adaptation during spaceflight and under altered mechanical loading conditions on Earth.
Long-duration human spaceflight will require medical systems capable of managing illness and injury without rapid evacuation or real-time assistance from Earth. Microgravity physiology, engineering limits, and communication delays reduce the feasibility of conventional surgery and favor imaging-based, minimally invasive approaches. Expeditionary interventional radiology can be defined as a practice model emphasizing image-guided, minimally invasive procedures delivered with compact equipment by small, cross-trained teams in resource-constrained environments. Research shows that astronauts and other non-specialists can obtain diagnostic-quality ultrasound images in microgravity, and analog studies demonstrate that individuals with little experience can learn key ultrasound-guided tasks after focused instruction. These findings support the feasibility of image-guided drainage, decompression, and vascular access as candidate strategies for managing acute conditions encountered during exploration missions. Remaining challenges include procedural ergonomics, equipment design, sterility, fluid containment, and development of autonomous guidance tools. This narrative review outlines a streamlined approach for adapting interventional radiology to spaceflight and highlights research needs for achieving procedural autonomy beyond Earth.
Harnessing transition metal dichalcogenides (TMDCs) for memristors provides a promising pathway toward high-density data storage and neuromorphic functionalities. Yet the single operation mode and insufficient on/off ratio extremely restrict the ultimate device performance. Here, we design and construct a high-order superlattice-based memristor by rolling up oxide/TMDCs heterostructures, which exhibits tunable resistive switching polarity and a high on/off ratio. Four types of heterostructures are created via fine-controlled oxygen plasma to in situ oxidize the top few layers into uniform transition metal oxide. Capillary forces in organic reagents are utilized to drive these heterostructures to spontaneously roll up. The as-formed high-order oxide/TMDCs superlattices with alternately stacked TMDCs and oxides are clearly resolved by the cross-section scanning transmission electron microscope and corresponding elemental mappings. With pre-set oxide layers supplying mobile oxygen atoms, bipolar resistive switching of the high-order superlattice-based memristors is realized in vertical tunneling current measurements. In contrast, when the top and bottom electrodes are arranged in an interleaved configuration, the spatial confinement of conductive filaments converts the switching behavior into a unipolar mode. Furthermore, this polarity-tunable memristor exhibits an outstanding on/off ratio of approximately 107 and a robust multilevel resistance performance. Our work opens a new avenue for the fundamental design of high-performance and multimodal memristors.
Coordination engineering of single-atom catalysts (SACs) is a powerful strategy to address durability and activity challenges in the acidic oxygen evolution reaction (OER). Here, we obtain two distinct Ir single-atom configurations on MoO3 support by regulating the second-shell coordination environment. Compared with the weakly interacting Ir─O─Mo structure, atomic pair sites formed through direct Ir─Mo coordination exhibit strong electronic coupling with the support, thereby enhancing atomic dispersion and structural stability. In situ experimental and theoretical studies reveal that the Ir─Mo pair sites trigger a new oxide-mediated pathway, in which dynamic hydroxyl spillover from Mo to Ir site effectively facilitates *OOH formation. This process breaks the linear scaling relationship between *OH and *OOH adsorption, lowering the energy barrier of the rate-limiting step and enabling superior OER kinetics. As a result, the IrO+Mo/MoO3 catalyst achieves outstanding stability for over 1500 h at 10 mA cm-2 in acidic electrolyte and sustains continuous operation for 300 h at 1.0 A cm-2 in the proton exchange membrane water electrolyzer. This work provides novel insights into the coordination engineering of SACs and opens a promising avenue for overcoming scaling limitations in acidic OER catalysis.
Fiber endoscopic imaging system exhibits high-precision imaging capability in extreme scenarios due to its flexibility and compatibility. The fiber bundles are naturally suitable to collect 2D intensity information, but it is difficult to directly obtain depth or angle information. Therefore, a large number of complex optical components are usually required to achieve dual-function imaging. In this work, we propose a single round-trip system with metasurface-integrated fiber bundle, namely the so-called Janus metafiber system. With the forward and reverse switching of the same optical path, we simultaneously achieving passive 2D imaging in the visible regime and active 3D depth sensing. The experiment shows high imaging fidelity and noise resilience benefiting from time-division acquisition between single-wavelength array scanning and polychromatic illumination. Especially, a 60° FOV and a divergence angle less than 2° has been verified in the interpolation optimized 3D depth imaging. Furthermore, the enhanced broadband depth-resolved synthetic imaging and edge detection are demonstrated combining the bimodal data. Our work enlightens potential applications in real-time biomedical diagnostics, LiDAR, and industrial inspection.
Pedestrian walking behaviour is intrinsic to individuals, yet it is influenced by external factors such as obstacles and the degree of crowding. It is precisely in crowded scenarios that pedestrian interactions lead to collective motions, such as lane formation or waves. Recently, the spontaneous development of collective counterclockwise motion has been reported in both dense and sparse human assemblies. Here we present five experimental studies of this phenomenon conducted across diverse conditions in Spain and Japan, demonstrating that counterclockwise bias in roaming pedestrians is a robust and reproducible feature and originates from individual tendencies rather than from collective interactions. These findings challenge the traditional view that social dynamics shape pedestrian motion, highlighting the existence of an intrinsic locomotor bias.
Cancer incidence is influenced by a combination of extrinsic and genetic factors. We hypothesized that cancers with similar incidence patterns may suggest shared etiologies. Age-standardized incidence rates for 36 cancer types across 185 countries were obtained from GLOBOCAN 2022. Pairwise Spearman's correlation coefficients were computed, and network clustering analyses were performed using six community detection algorithms: Leiden, Surprise, Walktrap, Girvan-Newman, Infomap, and spectral clustering. A dominant cluster was consistently identified, comprising kidney, pancreatic, colorectal, and thyroid cancers, as well as hematological malignancies. The second cluster comprised lung cancer, mesothelioma, melanoma, and non-melanoma skin cancer, which were grouped with head and neck cancers in some algorithms. Kaposi's sarcoma, nasopharyngeal cancer, and salivary gland cancer were classified individually. The dominant cluster showed significantly greater enrichment of shared mutational signatures (cosine similarity, p = 0.041) and recurrent mutation overlap (Jaccard similarity, p = 0.025) than expected by chance. Additionally, eigenvector centrality positively correlated with global cancer incidence rates. Overall, this unsupervised network analysis of global cancer epidemiology identifies biologically coherent clusters that reflect potentially shared etiological mechanisms and may inform public health intervention strategies.
Hemodialysis (HD) is the predominant treatment for end-stage renal disease (ESRD). Despite the efficacy of HD, the neurobiological underpinnings underlying high-risk complications remain unclear. In this study, using unsupervised fusion of functional and structural MRI, we identified a longitudinally altered default mode network (DMN)-insula pattern in ESRD receiving HD over 1-year follow-up (n = 39). This pattern was associated with cognition, and its related genes were enriched in biological processes involving DNA damage and repair, energy metabolism, and cellular activation. The baseline DMN-insula pattern demonstrated potential predictive value for follow-up cognition in ESRD. More importantly, these brain-cognition associations were validated in independent high-risk complications cohorts, including major depressive disorder (n = 60), mild cognitive impairment (n = 291), and Alzheimer's disease (n = 77) by extracting the corresponding brain features and assessing their correlations with cognition. Collectively, this study may help researchers better understand the underlying mechanisms of ESRD receiving HD from a multimodal neuroimaging and molecular perspective.
s: To investigate the hemodynamic consequences of renal artery ostium positioning following endovascular repair of juxtarenal aortic aneurysms (JAAAs) using the novel WeFlow-JAAA inner-branch system. Patient-specific computational fluid dynamics (CFD) analysis was performed on three postoperative JAAA cases treated with the WeFlow-JAAA endograft. For each case, four models systematically simulated progressive distal migration of the bilateral renal ostia, ranging from a proximal position near the celiac artery to their native anatomical locations. Renal perfusion rates, aortic flow patterns, and established wall shear stress (WSS)-derived metrics (time-averaged wall shear stress -TAWSS, oscillatory shear index - OSI, relative residence time - RRT) were quantitatively evaluated. Distal renal ostium positioning consistently yielded higher renal perfusion rates compared to proximal placements. However, this improved perfusion was associated with the development of potentially adverse hemodynamic conditions (characterized by low TAWSS and high OSI/RRT) on the perirenal aortic wall adjacent to the ostia. Conversely, proximal placements, while mitigating these adverse perirenal WSS patterns, compromised renal perfusion and generated pronounced flow disturbances in the infrarenal aorta distal to the termination of the inner-branch parallel segments. The preliminary findings suggest that renal ostium positioning after WeFlow-JAAA implantation may critically influence postoperative hemodynamics. The simulations indicate maximizing renal perfusion via distal placement may potentially expose the perirenal aortic wall to less favorable long-term WSS conditions. These results underscore the need for careful and potentially patient-specific consideration of device placement to appropriately balance perfusion and aortic wall remodeling risks in juxtarenal endovascular repair.
Coronary heart disease (CHD) and carotid artery disease (CAD) often co-occur. However, conventional diagnosis typically involves separate, site-by-site examinations after symptoms appear, leading to delayed intervention. In this work, we developed a wearable ultrasound system that enables synchronous monitoring of cardiac and carotid dynamics for comorbidity assessment. The system combines dual wearable ultrasound patches, a synchronous imaging strategy, artificial intelligence-based image processing algorithms, and human circuitry models to automatically extract and analyze key cardiac-carotid metrics, such as heart rate, pulse rate, cardiac volume, cardiac output, and carotid blood pressure. By evaluating the correlation of these metrics between modeling and measurements, we showed the feasibility of differentiating among healthy participants and patients with CAD, CHD, or CAD-CHD comorbidity. This integrated approach constitutes a promising framework for supporting the proactive assessment of coronary-carotid comorbidity.
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Nanofluid-based spectral filtering offers a promising approach to enhance photovoltaic/thermal (PV/T) system performance by utilizing the full solar spectrum. However, system optimization remains challenging due to complex nonlinear relationships between nanofluid parameters and overall performance. This study develops a prediction-optimization framework integrating deep neural networks (DNN) with genetic algorithms (GA) to accurately analyze multi-parameter interactions and achieve globally optimal designs for nanofluid-based PV/T systems. High-throughput datasets for three nanofluids (Ag, Au, Al) were constructed using theoretical calculations that combined Lorentz-Mie theory, Monte Carlo simulations, and a coupled opto-electro-thermal model. Three machine learning models-DNN, random forest (RF), and decision tree (DT)-were employed to predict key PV/T performance parameters. By synergizing machine learning with GA, a closed-loop prediction-optimization process was established to efficiently identify optimal design parameters. Among the models evaluated, the DNN demonstrated superior performance, achieving prediction accuracies above 99.48% for all three key performance indicators (ηpv, ηth, and MF), significantly outperforming the RF and DT models. Furthermore, SHAP analysis was conducted to quantify the contribution of each input feature and enhance model interpretability. Coupled with the GA, the DNN-GA framework successfully identified globally optimal design parameters for each nanofluid. For instance, for Ag nanofluid, the optimal combination (r = 4.02 nm, h = 9.91 mm, fv = 9.45 × 10-5) yielded a maximum MF value of 1.3603. This work presents an innovative machine learning framework for designing nanofluid filters in PV/T systems, which reduces reliance on iterative experimentation and accelerates the development of high-performance solar energy systems, demonstrating practical value.
A new performance index is proposed for ionic thermoelectric materials, to bridge the material properties and energy conversion efficiency in real-world application scenarios.
Halide perovskite single crystals are promising materials for radiation detection. However, their long-term operational stability under a high bias, particularly for methylammonium (MA)-based compositions, remains a challenge. Herein, we fabricate a structure of p-type/intrinsic/n-type/p-type diode (PINP diode) made of MAPbBr2.5Cl0.5 single crystals that significantly enhances stability. Compared to a conventional Au/intrinsic/Au structure, the dark current density of the PINP diode is markedly reduced from 698.2 nA cm-2 to 86.6 nA cm-2 under the bias of 200 V. In the proton-counting mode, the noise level is only 487 ± 50 electrons at 150 V bias. Thanks to the low noise and long-term stability, this MAPbBr2.5Cl0.5-based PINP diode achieves proton-counting detection for 60 MeV and 20 MeV protons. This work provides a viable strategy for developing stable perovskite single-crystal detectors capable of high-energy proton detection.
Graphite (Gr) has been considered as one of the most promising anode materials for potassium-ion batteries (PIBs) due to its low cost, high electrical conductivity, good chemical stability, and ability to reversibly form intercalation compounds with K+. However, the large ionic radius of K+ results in sluggish K-storage kinetics and irreversible disruption of the Gr structure during insertion/extraction, leading to unsatisfactory cycling stability and rate performance. In this work, a bromine-modified Gr-based composite (Br-Gr) was synthesized via a hexabromobenzene (HBB)-assisted one-step carbonization method. As a result, the optimized Br-Gr demonstrates a reversible discharge capacity of 310.1 mA h g-1 at a current density of 50 mA g-1 as well as a high-rate capacity of 109.5 mA h g-1 at 1000 mA g-1, along with excellent cycling stability and high reaction reversibility. This work presents a practical, cost-effective strategy for preparing high-performance Gr-based K-storage anode materials with promising commercial applications in PIBs.
The pore size of activated carbon significantly influences its formaldehyde adsorption capacity. Although water vapor is known to significantly affect this process, its role in carbons with different pore sizes remains unclear. This study employs a combined experimental and multiscale simulation approach to investigate the influence of water molecules on formaldehyde adsorption by activated carbons with varying pore sizes. Experimental results show that the modified activated carbon with an increased ultramicropore content exhibits superior formaldehyde adsorption performance, while elevated relative humidity leads to a noticeable decline in adsorption capacity. Multiscale simulations reveal that water clusters tend to accumulate and block ultramicropores, and mesopores lack sufficient confinement effects, both of which greatly reduce formaldehyde uptake. In contrast, the electrostatic interaction between water molecules and formaldehyde can moderately facilitate adsorption. The large micropore structure effectively alleviates water competitive adsorption, provides abundant adsorption sites through the confinement effect, and optimizes molecular mass transfer via wide channels. Combined with the electrostatic synergistic effect of water molecules, it maintains excellent formaldehyde adsorption capacity and humidity resistance. This study clarifies the structure-activity relationship between the pore structure of porous carbon and formaldehyde adsorption performance, providing theoretical support and design guidance for the development of high-efficiency carbon-based formaldehyde adsorbents applied in humid conditions.
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