{"title":"Reduction of tar, sulfur, chlorine and CO<sub>2</sub> in syngas produced by gasification of refuse-derived fuel pellets.","authors":"Matej Koritár, Juma Haydary","doi":"10.1038/s41598-025-03623-2","DOIUrl":"https://doi.org/10.1038/s41598-025-03623-2","url":null,"abstract":"<p><p>Effective waste management is an increasingly urgent global challenge, with gasification emerging as promising alternative to conventional disposal methods. However, the major challenge in thermochemical waste processing is the presence of contaminants in the product streams. Therefore, this study focuses on the experimental gasification of refuse-derived fuel (RDF) pellets, with the aim of characterizing the products, analyzing contaminant distribution, and purifying the syngas from multiple contaminants simultaneously. Gasification experiments were conducted in a two-stage batch reactor, and the produced syngas was purified using two continuous packed absorption columns. Yields of gaseous, liquid, and solid products were 52.5%, 23.5%, and 7.3%, respectively. Resulting char exhibited a lower heating value (LHV) of 18.24 MJ/kg and retained 76.8% of the sulfur and 35.8% of the chlorine from the RDF. Heavy metal concentrations in the char remained below environmental limits. Syngas achieved a maximum LHV of 11.9 MJ/Nm<sup>3</sup>. Its purification using aqueous solutions of NaOH and methyl-diethanolamine achieved removal efficiencies of 97.77% for H₂S and 43.06% for COS. Efficiency of HCl removal with NaOH solution ranged from 82.15% to 89.27%, also contributing to CO₂ removal. Tar content in the syngas was significantly reduced through catalytic treatment with Ni/activated carbon, achieving a maximum removal efficiency of 85.89%. Concentrations of key contaminants in syngas were reduced to 6.13 ppm for H<sub>2</sub>S, 41.58 ppm for COS, 19.37 mg/Nm<sup>3</sup> for HCl, and 2.11 g/Nm<sup>3</sup> for tar. These results demonstrate the feasibility of integrated gasification and multi-contaminant purification for producing cleaner syngas from RDF, advancing sustainable waste-to-energy solutions.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18446"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aymen M Al-Hejri, Archana Harsing Sable, Riyadh M Al-Tam, Mugahed A Al-Antari, Sultan S Alshamrani, Kaled M Alshmrany, Wedad Alatebi
{"title":"A hybrid explainable federated-based vision transformer framework for breast cancer prediction via risk factors.","authors":"Aymen M Al-Hejri, Archana Harsing Sable, Riyadh M Al-Tam, Mugahed A Al-Antari, Sultan S Alshamrani, Kaled M Alshmrany, Wedad Alatebi","doi":"10.1038/s41598-025-96527-0","DOIUrl":"https://doi.org/10.1038/s41598-025-96527-0","url":null,"abstract":"<p><p>Breast cancer remains a leading cause of mortality in women, underscoring the need for timely and accurate diagnosis. This paper addresses this challenge by introducing a comprehensive explainable federated learning framework for breast cancer prediction. We evaluate three deep learning approaches in both centralized and federated scenario settings: (1) individual artificial intelligence (AI) models, (2) high-level feature space ensemble models, and (3) a hybrid model combining global Vision Transformer (ViT) and local convolutional neural network (CNN) features. These models are assessed on binary, multi-class, and Breast Imaging Reporting and Data System (BI-RADS) classification tasks using a unique dataset encompassing real-world risk factors. In the federated scenario, we employ three clients with the same approaches as the centralized setting, aggregating their predictions using an AI global model. Explainable AI (XAI) technique is incorporated to enhance AI models' transparency. Our federated learning approach demonstrates superior performance, achieving accuracies of 98.65%, 97.30%, and 95.59% for binary, multi-class, and BI-RADS tasks, respectively. The proposed model, evaluated with a 95% Confidence Interval (CI) and Areas Under Curve (AUC) curves, registers top classifiers with an AUC of 0.970 [0.917-1]. Local Interpretable Model-Agnostic Explanations (LIME) XAI-based federated learning framework offers a promising solution for privacy-preserving and accurate breast cancer prediction in both research and clinical practice.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18453"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Younis Hamoudi Assaf, Abdulrazzak Akroot, Khaled Alnamasi, Mohamed A Ismail
{"title":"Investigation of heat transfer performance in heat exchangers using hybrid nanofluids and twisted tape inserts with fixed special rings.","authors":"Younis Hamoudi Assaf, Abdulrazzak Akroot, Khaled Alnamasi, Mohamed A Ismail","doi":"10.1038/s41598-025-02135-3","DOIUrl":"https://doi.org/10.1038/s41598-025-02135-3","url":null,"abstract":"<p><p>This study examines the thermo-hydraulic performance of a heat exchanger tube equipped with special fixed ring inserts and twisted tape elements, using a hybrid nanofluid composed of Al₂O₃-CuO/water. Simulations are carried out under turbulent flow conditions, covering Reynolds numbers from 6000 to 14,000. The impact of varying twisted tape torsion ratios (TR = 5, 10, and 15) and hybrid nanofluid volume concentrations (ϕ = 0.3%, 0.6%, and 0.9%) is systematically evaluated. A validated CFD model in ANSYS Fluent demonstrates strong agreement with benchmark data. The results show that, at Re = 14,000, inserting a twisted tape (TR = 5) into a plain tube boosts the Nusselt number (Nu) by 36.28% and the convective heat-transfer coefficient (h) by 36.3% compared to pure water. The tape promotes turbulence and disrupts the thermal boundary layer, enhancing convective heat transfer. However, these gains incur an 8.0% pressure-drop penalty (ΔP). Furthermore, the study highlights the critical role of nanofluid concentration in optimizing heat-exchanger performance. At a 0.9% volume fraction of Al₂O₃-CuO/water nanofluid added to the twisted-tape (TR = 5) configuration, the Nusselt number climbs an additional 3.2%, while the convective heat-transfer coefficient rises by 18.2%. This nanofluid boost comes with a modest 6.1% pressure-drop penalty (ΔP increases from 284.8 to 302.2 Pa) yet drives the thermal performance factor (TPF) from 1.38 to 3.29. These findings provide a comprehensive understanding of how synergistic passive heat transfer methods and nanofluids can be strategically utilized to enhance the efficiency of industrial heat exchangers.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18450"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Baodan Sun, Xinyi Zhang, Junhui Jiang, Jianguang Gong, Dan Lin
{"title":"Bayesian network structure learning by opposition-based learning.","authors":"Baodan Sun, Xinyi Zhang, Junhui Jiang, Jianguang Gong, Dan Lin","doi":"10.1038/s41598-025-03267-2","DOIUrl":"https://doi.org/10.1038/s41598-025-03267-2","url":null,"abstract":"<p><p>As a classical basic model for causal inference, Bayesian networks are of vital importance both in artificial intelligence with uncertainty and interpretability. The significant status of Bayesian networks in these research orientations depends on its topological structure, namely directed acyclic graphs. Bayesian network structure learning is a well-known NP-hard problem, and its computation accuracy is still worth being further studied. In this paper, we propose a new Bayesian network structure learning algorithm, OP-PSO-DE, which combines Particle Swarm Optimization(PSO) and Differential Evolution to search for the optimal structure. Since the computation complexity of BN structure learning increases exponentially with the number of nodes, the proposed algorithm incorporates opposition-based learning to narrow the search space of heuristic algorithms, which can effectively accelerate the searching process. Experimental results show that the proposed algorithm achieves better performances than other state-of-the-art structure learning algorithms when the sample size is 500. The source code of the paper can be found at this link: https://github.com/sunbaodan-hrbeu/paper_code .</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18447"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Study on multi-parameter optimization of seismic isolation bearings for continuous girder bridges considering interactions among key parameters.","authors":"Zhaolan Wei, Bowen Yang, Qixuan You, Konstantinos Daniel Tsavdaridis, Shaomin Jia","doi":"10.1038/s41598-025-02155-z","DOIUrl":"https://doi.org/10.1038/s41598-025-02155-z","url":null,"abstract":"<p><p>Traditional isolation design for continuous girder bridges often focuses on single-parameter tuning, overlooking the complex interactions among yield strength, pre-yield stiffness, and post-yield stiffness. This paper proposes a multi-parameter optimization method to systematically investigate the nonlinear influence of each parameter on the seismic performance of bridges. First, using a conventional particle swarm optimization (PSO) algorithm, the individual and combined effects of each parameter on key response indicators are identified. On this basis, an adaptive particle swarm optimization (APSO) algorithm with dynamic inertia weights and learning factors is introduced to broaden the search space, expedite convergence, and reduce the likelihood of becoming trapped in local optima. Numerical studies indicate that, compared with the standard PSO method, APSO can reduce the total number of iterations by up to 40% while maintaining solution accuracy. The underlying mechanism is that APSO preserves particle diversity and dynamically adjusts the balance between global and local searches, thereby rapidly identifying the optimal bearing configuration. Compared with single-parameter or orthogonal design methods, the APSO-based multi-parameter optimization strategy significantly enhances structural ductility, as reflected by notable reductions in pier-top displacement and pier-bottom shear force. These findings underscore the robustness and efficiency of APSO in designing isolation bearings for high-dimensional problem spaces.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18448"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fatma A Sayed, May Bin-Jumah, Arafa H Aly, V D Zhaketov, Mohammed Sallah, Zaky A Zaky
{"title":"Quasi periodic photonic crystal as gamma detector using Poly nanocomposite and porous silicon.","authors":"Fatma A Sayed, May Bin-Jumah, Arafa H Aly, V D Zhaketov, Mohammed Sallah, Zaky A Zaky","doi":"10.1038/s41598-025-02910-2","DOIUrl":"https://doi.org/10.1038/s41598-025-02910-2","url":null,"abstract":"<p><p>This research investigates the design and performance of quasi-periodic photonic crystals built using Thue-Morse sequences for gamma dosimetry applications. The structures were made of aluminum oxide and porous silicon infused with a poly(ethylene oxide) nanocomposite. The transmittance spectra of these crystals are heavily dependent on their structural evolution, with higher-generation structures exhibiting greater localization of defect modes. The study combines experimental data fitting with theoretical calculations to validate the optical behavior of the developed structures. These calculations were performed using the transfer matrix method over a wavelength range of 500-800 nm. Each structure's sensitivity and quality factor were evaluated in two radiation ranges-0-100 Gy and 100-200 Gy-to determine their potential as gamma dosimeters. The results demonstrate that the proposed structures are highly effective for dosimetry applications. They achieve an optimal balance between sensitivity (0.55 nm/Gy and 0.5 nm/Gy) and sharp defect modes, with quality factors of 1715.9 and 473, respectively. These findings suggest that Thue-Morse sequence-based photonic crystals can serve as highly tunable and efficient gamma radiation sensors.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18451"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P Raja, M Sakthivel, T Satish Kumar, Jana Petrů, Kanak Kalita
{"title":"Deep cryo treated tungsten carbide tools on AISI 1045 steel turning through grey relational analysis and preference selection index.","authors":"P Raja, M Sakthivel, T Satish Kumar, Jana Petrů, Kanak Kalita","doi":"10.1038/s41598-025-02263-w","DOIUrl":"https://doi.org/10.1038/s41598-025-02263-w","url":null,"abstract":"<p><p>Global competition and increasing environmental concerns have compelled manufacturing industries to reduce energy consumption and enhance product quality. This, in turn, helps increase the production rate. In this context, the machining performance is largely influenced by the selection of process parameters and the condition of the cutting tool. The present study is based on an experiment involving the use of an uncoated, deep cryogenically treated tungsten carbide tool for machining AISI 1045 steel. The outcomes were evaluated using Grey Relational Analysis (GRA) and the Preference Selection Index (PSI). Both ANOVA methods indicated that feed rate, cutting speed, the use of deep cryo-treated tools, and depth of cut had the most significant effects. The optimal parameter settings identified include a deep cryo-treated tool, a cutting speed of 120 m/min, a feed rate of 0.05 mm/rev, and a depth of cut of 1.00 mm. This approach demonstrated that the feed rate had the greatest influence on flank wear and surface roughness, both of which were also significantly affected by cutting speed and depth of cut. Moreover, the deep cryo-treated tool outperformed the untreated tool, resulting in reductions in surface roughness and flank wear by 17% and 7%, respectively. Deep Cryogenic Treatment (DCT) has thus shown promise in enhancing the performance of tungsten carbide cutting tools used in machining operations. This study specifically investigated the effect of DCT on tool wear and surface finish during the turning of AISI 1045 steel.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18452"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rui Hou, Quanfu Zhang, Mingna Duan, Shaobo Tang, Shuang Liu, Dandan Jiang, Chunhong Du, Xing Yang
{"title":"Characterization of the complete mitochondrial genome of Monticola rufiventris and phylogenetic implications.","authors":"Rui Hou, Quanfu Zhang, Mingna Duan, Shaobo Tang, Shuang Liu, Dandan Jiang, Chunhong Du, Xing Yang","doi":"10.1038/s41598-025-02187-5","DOIUrl":"https://doi.org/10.1038/s41598-025-02187-5","url":null,"abstract":"<p><p>Monticola rufiventris belongs to the order Passeriformes and the family Muscicapidae. As the largest group of birds, the phylogenetic relationships within Passeriformes have been a hot topic of research; however, studies on the genus Monticola within Passeriformes are relatively limited. This study presents the first comprehensive sequencing and analysis of the mitochondrial genome of M. rufiventris. Using Illumina Novaseq 6000 for paired-end sequencing, the results show that the mitochondrial genome of M. rufiventris is 16,803 bp, containing 13 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes, and 1 control region. Its structure is similar to that of known members of the Muscicapidae family, but there are some differences in gene size. Based on these data, we conducted mitochondrial assembly, selective pressure analysis, relative synonymous codon usage (RSCU) analysis, structural prediction of the 22 tRNAs, and phylogenetic tree construction. This study adds new data to the avian mitochondrial genome database, enhances the understanding of the Monticola mitochondrial genome, and provides valuable information for future research in avian taxonomy and phylogenetics.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18449"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Min Si Zhou, Wan Ru Zhang, Yan Dang, Fang Xu, Chen Yue Xu, Zhan Wang, Chun Sai Er Wang, Si Ying Zhu, Peng Li, Jing Wu, Hai Yun Shi
{"title":"Plasma inflammation-related proteins associated with anxiety and depression disorders in IBD patients.","authors":"Min Si Zhou, Wan Ru Zhang, Yan Dang, Fang Xu, Chen Yue Xu, Zhan Wang, Chun Sai Er Wang, Si Ying Zhu, Peng Li, Jing Wu, Hai Yun Shi","doi":"10.1038/s41598-025-03543-1","DOIUrl":"https://doi.org/10.1038/s41598-025-03543-1","url":null,"abstract":"<p><p>Up to 25-35% of patients with inflammatory bowel disease (IBD) suffer from anxiety or depression. Mood disorders are correlated with activated inflammatory response. However, changes of inflammation-related proteins in IBD patients with anxiety or depression disorders are still unclear. We aimed to depict the plasma proteomics characteristics of IBD patients with anxiety or depression. Adult patients diagnosed with IBD were prospectively enrolled, and the clinical data were obtained. The Hospital Anxiety and Depression Scale (HADS) was used to assess anxiety or depression levels. OLINK panel (Target 96 Inflammation) was used to quantify the plasma levels of inflammation-related proteins. Among the involved 142 IBD patients (median age 39.5, 42.96% female), 41 were comorbid with anxiety or depression symptoms. The levels of anxiety and depression symptoms in active phase group were significantly higher than those in quiescent group (P = 0.020). The anxiety and depression levels of IBD patients were positively correlated with fatigue levels (r = 0.713, P < 0.001), and negatively correlated with sleep quality (r = 0.499, P < 0.001) and quality of life (r =-0.692, P < 0.001). Plasma levels of 92 inflammation-related proteins were measured in 61 IBD patients. Up-regulated levels of fibroblast growth factor 23 (FGF-23) were found in IBD patients with anxiety or depression disorders, with an area under the curve (AUC) of 0.67(95%CI:0.53-0.81, P = 0.031). The plasma levels of C-C motif chemokine 20 (CCL20) and C-X-C motif chemokine 1 (CXCL1) were up-regulated in IBD patients with anxiety or depression, respectively, and the corresponding AUCs were 0.68 (95%CI:0.54-0.82, P = 0.036) and 0.70(95%CI:0.56-0.84, P = 0.017). Correlation analysis showed that the levels of anxiety and depression symptoms in IBD patients were negatively correlated with plasma Delta/Notch-like epidermal growth factor-related receptor (DNER) (r=-0.253, P = 0.047) and interleukin-8 (IL-8) (r=-0.275, P = 0.031) levels, and were positively correlated with the plasma levels of CXCL1 (r = 0.290, P = 0.022) and FGF-23 (r = 0.290, P = 0.022). In addition, negative correlation was found between plasma DNER levels and Mayo clinical scores in ulcerative colitis (UC) patients (r=-0.464, P = 0.001). Mood disorders are closely related to disease flare of IBD patients. The increasing levels of anxiety and depression in IBD patients are accompanied by graver fatigue, worse sleep quality and lower quality of life. Inflammation-related immune regulation is associated with the development of emotional disorders in IBD patients.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18445"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The aggregate index of systemic inflammation (AISI) and the risk of all-cause, cardiovascular, and cardio-cerebrovascular mortality in congestive heart failure patients: results from NHANES 1999-2018.","authors":"Xiaofang Bai, Lele Cheng, Huan Wang, Yangyang Deng, Xiaoning Tong, Wen Wen, Xiaojun Liu, Juan Zhou, Zuyi Yuan","doi":"10.1038/s41598-025-01196-8","DOIUrl":"10.1038/s41598-025-01196-8","url":null,"abstract":"<p><p>Congestive heart failure (CHF) is a prevalent cardiovascular disease, with increasing incidence and mortality rates associated with aging populations and rising rates of chronic diseases. Systemic inflammatory response is recognized to play a pivotal role in the pathogenesis of CHF, and the aggregate index of systemic inflammation (AISI) has garnered widespread attention as a comprehensive indicator reflecting inflammatory status in recent years. However, there is currently a lack of large-scale epidemiological studies investigating the relationship between AISI and all-cause, cardiovascular, and cardio-cerebrovascular mortality risks among CHF patients. This study aims to utilize data from the NHANES database spanning 1999 to 2018 to analyze the association between AISI and prognosis in CHF patients, aiming to provide new evidence to support research into the pathophysiology and clinical management of CHF. This study enrolled 1624 patients aged ≥ 18 years with congestive heart failure (CHF) from the National Health and Nutrition Examination Survey spanning 1999 to 2018. Patients were stratified into four groups based on the aggregate index of systemic inflammation (AISI). Survival differences among the groups were compared using log-rank tests and Kaplan-Meier curves. Additionally, multivariable Cox regression and restricted cubic spline analyses were employed to explore the relationship between AISI and all-cause, cardiovascular, and cardio-cerebrovascular mortality. Overall, during a mean follow-up of 76.4 ± 56.6 months among patients with congestive heart failure, a total of 828 participants (51.042%) died. Among these, 314 (19.389%) deaths were attributed to cardiovascular diseases, and 344 (21.226%) were related to cardio-cerebrovascular mortality. Kaplan-Meier analysis revealed significant differences in all-cause, cardiovascular, and cardio-cerebrovascular mortality among AISI quartiles (log-rank test: all P < 0.001). Multivariable adjusted models demonstrated that participants in the highest AISI quartile had increased risks of all-cause mortality (hazard ratio [HR] = 1.599, 95% confidence interval [CI] 1.595-1.602), cardiovascular mortality (HR = 1.070, 95% CI 1.066-1.074), and cardio-cerebrovascular mortality (HR = 1.173, 95% CI 1.168-1.177) compared to those in the lowest quartile. Additionally, restricted cubic spline analysis indicated a nonlinear association between AISI and all-cause mortality (P = 0.0064), with an inflection point at AISI 8.66. On the left flank of the inflection point, each twofold increase in AISI was associated with a 19.6% higher risk of all-cause mortality (HR = 1.196, 95% CI 0.930-1.538), while on the right flank, there was a 126.2% increase (HR = 2.262, 95% CI 1.506-3.395). Furthermore, each twofold change in AISI was nonlinearly associated with a 60.2% higher risk of cardiovascular mortality (HR = 1.602, 95% CI 1.075-2.388) and a 56.6% higher risk of cardio-cerebrovascular mortality (HR = 1.566, 95%","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"18282"},"PeriodicalIF":3.8,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144143638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}