Short-Term Exposure to Fine Particulate Matter and Ozone: Source Impacts and Attributable Mortalities.

Short-term exposure to particles with aerodynamic diameters less than 2.5 µm (PM2.5) and ozone (O3) are important risk factors for human health. Despite the awareness of reducing attributable health burden, region-specific and source-specific strategies remain less explored due to the gap between precursor emissions and health effects. In this study, we isolate the health burden of individual sector sources of PM2.5 and O3 precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), across the globe. Specifically, we estimate mortalities attributable to short-term exposure using machine-learning-based daily exposure estimates and quantify sectoral impacts using chemical transport model simulations. Globally, short-term exposure to PM2.5 and O3 result in 713.5 (95% Confidence Interval: 598.8-843.3) thousand and 496.3 (371.3-646.1) thousand mortalities in 2019, respectively, of which 12.5% are contributed by fuel-related NOx emissions from transportation, energy, and industry. Sectoral impacts from anthropogenic NOx and VOC emissions on health burden vary significantly among seasons and regions, requiring a target shift from transportation in winter to industry in summer for East Asia, for instance. Emission control and health management are additionally complicated by unregulated natural influences during climatic events. Fire-sourced NOx and VOC emissions, respectively, contribute to 8.5 (95% CI: 6.2-11.7) thousand and 4.8 (3.6-5.9) thousand PM2.5 and O3 mortalities, particularly for tropics with high vulnerability to climate change. Additionally, biogenic VOC emissions during heatwaves contribute to 1.8 (95% CI: 1.5-2.2) thousand O3-introduced mortalities, posing challenges in urban planning for high-income regions, where biogenic contributions to health burden during heatwaves are 13% of anthropogenic contributions annually. Our study provides important implications for temporally dynamic and sector-targeted emission control and health management strategies, which are of urgency under the projection of continuously increasing energy consumption and changing climate.

Insights into dynamic structural evolution and its sodium storage mechanisms of P2/P3 composite cathode materials for sodium-ion batteries.

Cobalt substitution for manganese sites in Na0.44MnO2 initiates a dynamic structural evolution process, yielding a composite cathode material comprising intergrown P2 and P3 phases. The novel P2/P3 composite cathode exhibits a reversible phase transition process during Na+ extraction/insertion, showcasing its attractive battery performance in sodium-ion batteries.

Research on the Construction of a Series of Transition Metal-Substituted Keggin-Type TMSPOMs@PCN-224 Composites through the Encapsulation Method and Their Electron Transfer Mechanism in CO2RR.

In order to take advantage of the distinct reversible multielectron transfer properties of polyoxometalates (POMs) and increase the electron density at the active sites during the electrochemical reduction of CO2 (CO2RR), a range of transition metal-doped polyoxometalates (TMSPOMs) was entrapped within the porphyrin-based framework of PCN-224 via an encapsulation method, known as TMSPOMs@PCN-224 (TMSPOMs = [XW11O39MII(H2O)]n-, [XW11O40VIV]n-, M = CoII, MnII; X = Si, n = 6; X = P, n = 5). The central elements (Si, P) and the incorporated transition metals (VIV, CoII, and MnII) both play a role in adjusting the electronic structure and electron transfer during the CO2RR process. Remarkably, the composite material with cobalt substitution displayed significantly improved performance. Through fine-tuning the POM loading, the electrocatalytic activity was optimized, leading to an impressive Faradaic efficiency for CO production (FECO) of 89.9% for SiW11Co@PCN-224, a significant improvement compared to the 12.1% FECO of PCN-224. Furthermore, the electrochemical stability of this catalyst was demonstrated over 20 h. Comparative analyses involving six composite materials indicated a relationship between the negative charge of the polyanions and their ability to facilitate effective electron transfer, ultimately enhancing the catalyst's performance. Meanwhile, these findings were supported by density functional theory (DFT) calculations.

P-doped spherical hard carbon with high initial coulombic efficiency and enhanced capacity for sodium ion batteries.

Hard carbon (HC) is one of the most promising anode materials for sodium-ion batteries (SIBs) due to its cost-effectiveness and low-voltage plateau capacity. Heteroatom doping is considered as an effective strategy to improve the sodium storage capacity of HC. However, most of the previous heteroatom doping strategies are performed at a relatively low temperature, which could not be utilized to raise the low-voltage plateau capacity. Moreover, extra doping of heteroatoms could create new defects, leading to a low initial coulombic efficiency (ICE). Herein, we propose a repair strategy based on doping a trace amount of P to achieve a high capacity along with a high ICE. By employing the cross-linked interaction between glucose and phytic acid to achieve the in situ P doped spherical hard carbon, the obtained PHC-0.2 possesses a large interlayer space that facilitates Na+ storage and transportation. In addition, doping a suitable amount of P could repair some defects in carbon layers. When used as an anode material for SIBs, the PHC-0.2 exhibits an enhanced reversible capacity of 343 mA h g-1 at 20 mA g-1 with a high ICE of 92%. Full cells consisting of a PHC-0.2 anode and a Na2Fe0.5Mn0.5[Fe(CN)6] cathode exhibited an average potential of 3.1 V with an initial discharge capacity of 255 mA h g-1 and an ICE of 85%. The full cell displays excellent cycling stability with a capacity retention of 80.3% after 170 cycles. This method is simple and low-cost, which can be extended to other energy storage materials.

Stratospheric influence on surface ozone pollution in China.

Events of stratospheric intrusions to the surface (SITS) can lead to severe ozone (O3) pollution. Still, to what extent SITS events impact surface O3 on a national scale over years remains a long-lasting question, mainly due to difficulty of resolving three key SITS metrics: frequency, duration and intensity. Here, we identify 27,616 SITS events over China during 2015-2022 based on spatiotemporally dense surface measurements of O3 and carbon monoxide, two effective indicators of SITS. An overview of the three metrics is presented, illustrating large influences of SITS on surface O3 in China. We find that SITS events occur preferentially in high-elevation regions, while those in plain regions are more intense. SITS enhances surface O3 by 20 ppbv on average, contributing to 30-45% of O3 during SITS periods. Nationally, SITS-induced O3 peaks in spring and autumn, while over 70% of SITS events during the warm months exacerbate O3 pollution. Over 2015-2022, SITS-induced O3 shows a declining trend. Our observation-based results can have implications for O3 mitigation policies in short and long terms.

Interfacial Spinel Local Interlocking Strategy Toward Structural Integrity in P3 Oxide Cathodes.

P3-layered transition oxide cathodes have garnered considerable attention owing to their high initial capacity, rapid Na+ kinetics, and less energy consumption during the synthesis process. Despite these merits, their practical application is hindered by the substantial capacity degradation resulting from unfavorable structural transformations, Mn dissolution and migration. In this study, we systematically investigated the failure mechanisms of P3 cathodes, encompassing Mn dissolution, migration, and the irreversible P3-O3' phase transition, culminating in severe structural collapse. To address these challenges, we proposed an interfacial spinel local interlocking strategy utilizing P3/spinel intergrowth oxide as a proof-of-concept material. As a result, P3/spinel intergrowth oxide cathodes demonstrated enhanced cycling performance. The effectiveness of suppressing Mn migration and maintaining local structure of interfacial spinel local interlocking strategy was validated through depth-etching X-ray photoelectron spectroscopy, X-ray absorption spectroscopy, and in situ synchrotron-based X-ray diffraction. This interfacial spinel local interlocking engineering strategy presents a promising avenue for the development of advanced cathode materials for sodium-ion batteries.

Prelimbic cortex-nucleus accumbens core projection positively regulates itch and itch-related aversion.

Itch is one of the most common clinical symptoms in patients with diseases of the skin, liver, or kidney, and it strongly triggers aversive emotion and scratching behavior. Previous studies have confirmed the role of the prelimbic cortex (Prl) and the nucleus accumbens core (NAcC), which are reward and motivation regulatory centers, in the regulation of itch. However, it is currently unclear whether the Prl-NAcC projection, an important pathway connecting these two brain regions, is involved in the regulation of itch and its associated negative emotions. In this study, rat models of acute neck and cheek itch were established by subcutaneous injection of 5-HT, compound 48/80, or chloroquine. Immunofluorescence experiments determined that the number of c-Fos-immunopositive neurons in the Prl increased during acute itch. Chemogenetic inhibition of Prl glutamatergic neurons or Prl-NAcC glutamatergic projections can inhibit both histaminergic and nonhistaminergic itch-scratching behaviors and rectify the itch-related conditioned place aversion (CPA) behavior associated with nonhistaminergic itch. The Prl-NAcC projection may play an important role in the positive regulation of itch-scratching behavior by mediating the negative emotions related to itch.

Nonflammable Succinonitrile-Based Deep Eutectic Electrolyte for Intrinsically Safe High-Voltage Sodium-Ion Batteries.

Intrinsically safe sodium-ion batteries are considered as a promising candidate for large-scale energy storage systems. However, the high flammability of conventional electrolytes may pose serious safety threats and even explosions. Herein, a strategy of constructing a deep eutectic electrolyte is proposed to boost the safety and electrochemical performance of succinonitrile (SN)-based electrolyte. The strong hydrogen bond between S═O of 1,3,2-dioxathiolane-2,2-dioxide (DTD) and the α-H of SN endows the enhanced safety and compatibility of SN with Lewis bases. Meanwhile, the DTD participates in the inner Na+ sheath and weakens the coordination number of SN. The unique solvation configuration promotes the formation of robust gradient inorganic-rich electrode-electrolyte interphase, and merits stable cycling of half-cells in a wide temperature range, with a capacity retention of 82.8% after 800 cycles (25 °C) and 86.3% after 100 cycles (60 °C). Correspondingly, the full cells deliver tremendous improvement in cycling stability and rate performance.

Feruloylated Oligosaccharides Prevented Influenza-Induced Lung Inflammation via the RIG-I/MAVS/TRAF3 Pathway.

Uncontrolled inflammation contributes significantly to the mortality in acute respiratory infections. Our previous research has demonstrated that maize bran feruloylated oligosaccharides (FOs) possess notable anti-inflammatory properties linked to the NF-kB pathway regulation. In this study, we clarified that the oral administration of FOs moderately inhibited H1N1 virus infection and reduced lung inflammation in influenza-infected mice by decreasing a wide spectrum of cytokines (IFN-α, IFN-ß, IL-6, IL-10, and IL-23) in the lungs. The mechanism involves FOs suppressing the transduction of the RIG-I/MAVS/TRAF3 signaling pathway, subsequently lowering the expression of NF-κB. In silico analysis suggests that FOs have a greater binding affinity for the RIG-I/MAVS signaling complex. This indicates that FOs have potential as promising targets for immune modulation. Moreover, in MAVS knockout mice, we confirmed that the anti-inflammatory function of FOs against influenza depends on MAVS. Comprehensive analysis using 16S rRNA gene sequencing and metabolite profiling techniques showed that FOs have the potential to restore immunity by modulating the gut microbiota. In conclusion, our study demonstrates that FOs are effective anti-inflammatory phytochemicals in inhibiting lung inflammation caused by influenza. This suggests that FOs could serve as a potential nutritional strategy for preventing the H1N1 virus infection and associated lung inflammation.

Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001-2018).

Tropospheric nitrogen dioxide (NO2) poses a serious threat to the environmental quality and public health. Satellite NO2 observations have been continuously used to monitor NO2 variations and improve model performances. However, the accuracy of satellite NO2 retrieval depends on the knowledge of aerosol optical properties, in particular for urban agglomerations accompanied by significant changes in aerosol characteristics. In this study, we investigate the impacts of aerosol composition on tropospheric NO2 retrieval for an 18 year global data set from Global Ozone Monitoring Experiment (GOME)-series satellite sensors. With a focus on cloud-free scenes dominated by the presence of aerosols, individual aerosol composition affects the uncertainties of tropospheric NO2 columns through impacts on the aerosol loading amount, relative vertical distribution of aerosol and NO2, aerosol absorption properties, and surface albedo determination. Among aerosol compositions, secondary inorganic aerosol mostly dominates the NO2 uncertainty by up to 43.5% in urban agglomerations, while organic aerosols contribute significantly to the NO2 uncertainty by -8.9 to 37.3% during biomass burning seasons. The possible contrary influences from different aerosol species highlight the importance and complexity of aerosol correction on tropospheric NO2 retrieval and indicate the need for a full picture of aerosol properties. This is of particular importance for interpreting seasonal variations or long-term trends of tropospheric NO2 columns as well as for mitigating ozone and fine particulate matter pollution.

The detection methods currently available for protein aggregation in neurological diseases.

Protein aggregation is a pathological feature in various neurodegenerative diseases and is thought to play a crucial role in the onset and progression of neurological disorders. This pathological phenomenon has attracted increasing attention from researchers, but the underlying mechanism has not been fully elucidated yet. Researchers are increasingly interested in identifying chemicals or methods that can effectively detect protein aggregation or maintain protein stability to prevent aggregation formation. To date, several methods are available for detecting protein aggregates, including fluorescence correlation spectroscopy, electron microscopy, and molecular detection methods. Unfortunately, there is still a lack of methods to observe protein aggregation in situ under a microscope. This article reviews the two main aspects of protein aggregation: the mechanisms and detection methods of protein aggregation. The aim is to provide clues for the development of new methods to study this pathological phenomenon.

Interfacial Engineering for Oriented Crystal Growth toward Dendrite-Free Zn Anode for Aqueous Zinc Metal Battery.

Zn deposition with a surface-preferred (002) crystal plane has attracted extensive attention due to its inhibited dendrite growth and side reactions. However, the nucleation and growth of the Zn(002) crystal plane are closely related to the interfacial properties. Herein, oriented growth of Zn(002) crystal plane is realized on Ag-modified surface that is directly visualized by in situ atomic force microscopy. A solid solution HCP-Zn (~1.10 at. % solubility of Ag, 30 °C) is formed on the Ag coated Zn foil (Zn@Ag) and possesses the same crystal structure as Zn to reduce its nucleation barrier caused by their lattice mismatch. It merits oriented Zn deposition and corrosion-resistant surface, and presents long cycling stability in symmetric cells and full cells coupled with V2O5 cathode. This work provides insights into interfacial regulation of Zn anodes for high-performance aqueous zinc metal batteries.

Deep learning-assisted detection and segmentation of intracranial hemorrhage in noncontrast computed tomography scans of acute stroke patients: a systematic review and meta-analysis.

BACKGROUND: Deep learning (DL)-assisted detection and segmentation of intracranial hemorrhage stroke in noncontrast computed tomography (NCCT) scans are well-established, but evidence on this topic is lacking. MATERIALS AND METHODS: PubMed and Embase databases were searched from their inception to November 2023 to identify related studies. The primary outcomes included sensitivity, specificity, and the Dice Similarity Coefficient (DSC); while the secondary outcomes were positive predictive value (PPV), negative predictive value (NPV), precision, area under the receiver operating characteristic curve (AUROC), processing time, and volume of bleeding. Random-effect model and bivariate model were used to pooled independent effect size and diagnostic meta-analysis data, respectively. RESULTS: A total of 36 original studies were included in this meta-analysis. Pooled results indicated that DL technologies have a comparable performance in intracranial hemorrhage detection and segmentation with high values of sensitivity (0.89, 95% CI: 0.88-0.90), specificity (0.91, 95% CI: 0.89-0.93), AUROC (0.94, 95% CI: 0.93-0.95), PPV (0.92, 95% CI: 0.91-0.93), NPV (0.94, 95% CI: 0.91-0.96), precision (0.83, 95% CI: 0.77-0.90), DSC (0.84, 95% CI: 0.82-0.87). There is no significant difference between manual labeling and DL technologies in hemorrhage quantification (MD 0.08, 95% CI: -5.45-5.60, P =0.98), but the latter takes less process time than manual labeling (WMD 2.26, 95% CI: 1.96-2.56, P =0.001). CONCLUSION: This systematic review has identified a range of DL algorithms that the performance was comparable to experienced clinicians in hemorrhage lesions identification, segmentation, and quantification but with greater efficiency and reduced cost. It is highly emphasized that multicenter randomized controlled clinical trials will be needed to validate the performance of these tools in the future, paving the way for fast and efficient decision-making during clinical procedure in patients with acute hemorrhagic stroke.

A conductive and sodiophilic Ag coating layer regulating Na deposition behaviors for highly reversible sodium metal batteries.

Sodium metal batteries have attracted increasing interest recently, but suffer from severe dendrite growth caused by uneven Na plating/stripping behavior, which may result in the piercing of the membrane, with short circuiting and even cause explosions. Herein, a conductive and sodiophilic Ag coating layer is introduced to regulate Na deposition behaviors for highly reversible sodium metal batteries. Ag coated Zn foil with enhanced sodiophilicity, rapid Na+ transfer kinetics and superior electronic conductivity guarantee the homogenized Na+ ion and electric field distribution. This enables remarkably low overpotentials and uniform Na plating/stripping behavior with ultrahigh Coulombic efficiency of 99.9% during 500 cycles. As expected, the enhanced electrochemical performance of the anode-less battery and anode-free battery coupled with Prussian blue is achieved with the help of Ag coating. This work emphasizes the role of the conductive and sodiophilic coating layer in regulating the Na deposition behaviors for highly reversible sodium metal batteries.

Deep learning-based quantification of total bleeding volume and its association with complications, disability, and death in patients with aneurysmal subarachnoid hemorrhage.

OBJECTIVE: The relationships between immediate bleeding severity, postoperative complications, and long-term functional outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH) remain uncertain. Here, the authors apply their recently developed automated deep learning technique to quantify total bleeding volume (TBV) in patients with aSAH and investigate associations between quantitative TBV and secondary complications, adverse long-term functional outcomes, and death. METHODS: Electronic health record data were extracted for adult patients admitted to a single institution within 72 hours of aSAH onset between 2018 and 2021. An automatic deep learning model was used to fully segment and quantify TBV on admission noncontrast head CT images. Patients were subgrouped by TBV quartile, and multivariable logistic regression, restricted cubic splines, and subgroup analysis were used to explore the relationships between TBV and each clinical outcome. RESULTS: A total of 819 patients were included in the study. Sixty-six (8.1%) patients developed hydrocephalus, while 43 (5.3%) experienced rebleeding, 141 (17.2%) had delayed cerebral ischemia, 88 (10.7%) died in the 12 months after discharge, and 208 (25.7%) had a modified Rankin Scale score ≥ 3 12 months after discharge. On multivariable analysis, patients in the highest TBV quartile (> 37.94 ml) had an increased risk of hydrocephalus (adjusted OR [aOR] 4.38, 95% CI 1.61-11.87; p = 0.004), rebleeding (aOR 3.26, 95% CI 1.03-10.33; p = 0.045), death (aOR 6.92, 95% CI 1.89-25.37; p = 0.004), and 12-month disability (aOR 3.30, 95% CI 1.62-6.72; p = 0.001) compared with the lowest TBV quantile (< 8.34 ml). The risks of hydrocephalus (nonlinear, p = 0.025), rebleeding, death, and disability (linear, p > 0.05) were positively associated with TBV by restricted cubic splines. In subgroup analysis, TBV had a stronger effect on 12-month outcome in female than male patients (p for interaction = 0.0499) and on rebleeding prevalence in patients with endovascular coiling than those with surgical clipping (p for interaction = 0.008). CONCLUSIONS: Elevated TBV is associated with a greater risk of hydrocephalus, rebleeding, death, and poor prognosis.

Comparative assessment of leaf photosynthetic capacity datasets for estimating terrestrial gross primary productivity.

The maximum Rubisco carboxylation rate normalized to 25 °C (Vcmax25) is a key parameter in terrestrial biosphere models for simulating carbon cycling. Recently, global distributions of Vcmax25 have been derived through various methods and different data, including field measurements, ecological optimality theory (EOT), leaf chlorophyll content (LCC), and solar-induced chlorophyll fluorescence (SIF). However, direct validation poses challenges due to high uncertainty arising from limited ground-based observations. This study conducted an indirect evaluation of four Vcmax25 datasets by assessing the accuracy of gross primary productivity (GPP) simulated using the Biosphere-atmosphere Exchange Process Simulator (BEPS) at both site and global scales. Results indicate that, compared to utilizing Vcmax25 fixed by plant functional types (PFT) derived from field measurements, incorporating Vcmax25 derived from SIF and LCC (SIF + LCC), or solely LCC, into BEPS significantly reduces simulated errors in the annual total GPP, with a 23.2 %-25.1 % decrease in the average absolute bias across 196 FLUXNET2015 sites. Daily GPP for evergreen needleleaf forests, deciduous broadleaf forests, shrublands, grasslands, and croplands shows a 7.8 %-27.6 % decrease in absolute bias, primarily attributed to reduced simulation errors during off-peak seasons of vegetation growth. Conversely, the annual total GPP error simulated using EOT-derived Vcmax25 increases slightly (2.2 %) compared to that simulated using PFT-fixed Vcmax25. This is primarily due to a significant overestimation in evergreen broadleaf forests and underestimation in croplands, despite slight increased accuracy for other PFTs. The global annual GPP simulated using Vcmax25 with seasonal variations (i.e., LCC Vcmax25 and SIF + LCC Vcmax25) yields a 4.3 %-7.3 % decrease compared to that simulated using PFT-fixed Vcmax25. Compared to FLUXCOM and GOSIF GPP products, the GPP simulated based on SIF + LCC Vcmax25 and LCC Vcmax25 demonstrates better consistency (R2 = 0.91-0.93, RMSE = 314.2-376.6 g C m-2 yr-1). This study underscores the importance of accurately characterizing the spatiotemporal variations in Vcmax25 for the accurate simulation of global vegetation productivity.

Revealing the effect of conductive carbon materials on the sodium storage performance of sodium iron sulfate.

Na2Fe2(SO4)3 (NFS), as a promising cathode for sodium-ion batteries, is still plagued by its poor intrinsic conductivity. In general, hybridization with carbon materials is an effective strategy to improve the sodium storage performance of NFS. However, the role of carbon materials in the electrochemical performance of NFS cathode materials has not been thoroughly investigated. Herein, the effect of carbon materials was revealed by employing various conductive carbon materials as carbon sources. Among these, the NFS coated with Ketjen Black (NFS@KB) shows the largest specific surface area, which is beneficial for electrolyte penetration and rapid ionic/electronic migration, leading to improved electrochemical performance. Therefore, NFS@KB shows a long cycle life (74.6 mA h g-1 after 1000 cycles), superior rate performance (61.5 mA h g-1 at a 5.0 A g-1), and good temperature tolerance (-10 °C to 60 °C). Besides, the practicality of the NFS@KB cathode was further demonstrated by assembling a NFS@KB//hard carbon full cell. Therefore, this research indicates that a suitable carbon material for the NFS cathode can greatly activate the sodium storage performance.

Routes to high-performance layered oxide cathodes for sodium-ion batteries.

Sodium-ion batteries (SIBs) are experiencing a large-scale renaissance to supplement or replace expensive lithium-ion batteries (LIBs) and low energy density lead-acid batteries in electrical energy storage systems and other applications. In this case, layered oxide materials have become one of the most popular cathode candidates for SIBs because of their low cost and comparatively facile synthesis method. However, the intrinsic shortcomings of layered oxide cathodes, which severely limit their commercialization process, urgently need to be addressed. In this review, inherent challenges associated with layered oxide cathodes for SIBs, such as their irreversible multiphase transition, poor air stability, and low energy density, are systematically summarized and discussed, together with strategies to overcome these dilemmas through bulk phase modulation, surface/interface modification, functional structure manipulation, and cationic and anionic redox optimization. Emphasis is placed on investigating variations in the chemical composition and structural configuration of layered oxide cathodes and how they affect the electrochemical behavior of the cathodes to illustrate how these issues can be addressed. The summary of failure mechanisms and corresponding modification strategies of layered oxide cathodes presented herein provides a valuable reference for scientific and practical issues related to the development of SIBs.

Explainable machine learning in outcome prediction of high-grade aneurysmal subarachnoid hemorrhage.

OBJECTIVE: Accurate prognostic prediction in patients with high-grade aneruysmal subarachnoid hemorrhage (aSAH) is essential for personalized treatment. In this study, we developed an interpretable prognostic machine learning model for high-grade aSAH patients using SHapley Additive exPlanations (SHAP). METHODS: A prospective registry cohort of high-grade aSAH patients was collected in one single-center hospital. The endpoint in our study is a 12-month follow-up outcome. The dataset was divided into training and validation sets in a 7:3 ratio. Machine learning algorithms, including Logistic regression model (LR), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), were employed to develop a prognostic prediction model for high-grade aSAH. The optimal model was selected for SHAP analysis. RESULTS: Among the 421 patients, 204 (48.5%) exhibited poor prognosis. The RF model demonstrated superior performance compared to LR (AUC = 0.850, 95% CI: 0.783-0.918), SVM (AUC = 0.862, 95% CI: 0.799-0.926), and XGBoost (AUC = 0.850, 95% CI: 0.783-0.917) with an AUC of 0.867 (95% CI: 0.806-0 .929). Primary prognostic features identified through SHAP analysis included higher World Federation of Neurosurgical Societies (WFNS) grade, higher modified Fisher score (mFS) and advanced age, were found to be associated with 12-month unfavorable outcome, while the treatment of coiling embolization for aSAH drove the prediction towards favorable prognosis. Additionally, the SHAP force plot visualized individual prognosis predictions. CONCLUSIONS: This study demonstrated the potential of machine learning techniques in prognostic prediction for high-grade aSAH patients. The features identified through SHAP analysis enhance model interpretability and provide guidance for clinical decision-making.