综合性期刊最新文献

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A hybrid self attentive linearized phrase structured transformer based RNN for financial sentence analysis with sentence level explainability. 基于混合自关注线性化短语结构变压器的RNN金融句子分析,具有句子级可解释性。
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-09265-8
Md Tanzib Hosain, Md Kishor Morol, Md Jakir Hossen
{"title":"A hybrid self attentive linearized phrase structured transformer based RNN for financial sentence analysis with sentence level explainability.","authors":"Md Tanzib Hosain, Md Kishor Morol, Md Jakir Hossen","doi":"10.1038/s41598-025-09265-8","DOIUrl":"https://doi.org/10.1038/s41598-025-09265-8","url":null,"abstract":"<p><p>As financial institutions want openness and accountability in their automated systems, the task of understanding model choices has become more crucial in the field of financial text analysis. In this study, we propose xFiTRNN, a hybrid model that integrates self-attention mechanisms, linearized phrase structure, and a contextualized transformer-based Recurrent Neural Network (RNN) to enhance both model performance and explainability in financial sentence prediction. The model captures subtle contextual information from financial texts while maintaining explainability. xFiTRNN provides transparent, sentence-level insights into predictions by incorporating advanced explainability techniques such as LIME (Local Interpretable Model-agnostic Explanations) and Anchors. Extensive evaluations on benchmark financial datasets demonstrate that xFiTRNN not only achieves a remarkable prediction performance but also enhances explainability in the financial sector. This work highlights the potential of hybrid transformer-based RNN architectures for fostering more accountable and understandable Artificial Intelligence (AI) applications in finance.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23893"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565133","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}
引用次数: 0
Circadian and temporal eating patterns in relation to metabolic syndrome in Iranian women. 伊朗妇女与代谢综合征相关的昼夜和时间饮食模式
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-09427-8
Azadeh Lesani, Mansooreh Sadat Mojani-Qomi
{"title":"Circadian and temporal eating patterns in relation to metabolic syndrome in Iranian women.","authors":"Azadeh Lesani, Mansooreh Sadat Mojani-Qomi","doi":"10.1038/s41598-025-09427-8","DOIUrl":"https://doi.org/10.1038/s41598-025-09427-8","url":null,"abstract":"<p><p>Late energy intake (EI) is linked to increased obesity; however, the relationship between circadian eating patterns-including timing (morning vs. evening) energy and macronutrients, eating frequency, and eating window duration-and metabolic syndrome (MetS) in Iranian women remains insufficiently elucidated, particularly across age groups, menopausal statuses, and diurnal preference. In this cross-sectional study, dietary intake of 574 women aged 20 to 60 years from Tehran was assessed using three 24-hour dietary recalls. diurnal preference was evaluated through the Morningness-Eveningness Questionnaire. The analysis focused on eveningness in EI and macronutrient intake (%evening - %morning), eating occasions (EOs), and eating window duration. Anthropometric measurements, blood pressure, glucose, and lipid levels, were recorded. Generalized linear regression was utilized. Eveningness of EI was related to increased MetS risk T (tertile) 3 vs.T1 (ORs (95% CIs); 0.35 (0.11-0.62), p = 0.03). Also, the number of EOs T3 vs.T1 ( -0.68 (-1.32 - -0.23), p = 0.02) was related to decreased MetS. Eveningness of EI was linked to risk of elevated fasting blood glucose, T3 vs. T1 (0.46 (0.09-0.91), p = 0.02), Additionally, T3 vs. T1 in the Eveningness of protein showed a significant decrease in TG, (-0.56 (-1.01 - -0.12); p = 0.01). No associations were found in stratified by age, menopausal status, and chronotype. Consuming fewer meals along with a higher evening energy-might from non-protein sources-might be associated with increased the risk of MetS cross-sectionally, emphasizing the need for longitudinal studies to deepen our understanding of these relationships.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23954"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565137","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}
引用次数: 0
Cognitive abstraction increases prosociality when loyalty is valued lowly, but decreases prosociality when loyalty is valued highly. 当忠诚被低估时,认知抽象会增加亲社会性,而当忠诚被高估时,认知抽象会降低亲社会性。
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-09158-w
Gijs van Houwelingen, Marius van Dijke
{"title":"Cognitive abstraction increases prosociality when loyalty is valued lowly, but decreases prosociality when loyalty is valued highly.","authors":"Gijs van Houwelingen, Marius van Dijke","doi":"10.1038/s41598-025-09158-w","DOIUrl":"https://doi.org/10.1038/s41598-025-09158-w","url":null,"abstract":"<p><p>Many studies show that people donate more to charitable causes that are presented in concrete (vs. abstract) terms; yet other research suggests that cognitive abstraction (vs. concreteness) encourages prosocial behavior. We propose that abstract cognition facilitates prosocial behavior among people who lowly value loyalty (i.e., those who value impartiality); concrete cognition should facilitate prosocial behaviors among people who highly value loyalty. Across three experiments and one cross-sectional survey in which we operationalize cognitive abstraction (vs. concreteness), valuing loyalty, and prosocial behavior in different ways, we consistently find that abstraction facilitates prosocial behaviors among people who lowly value loyalty. In two of the four studies, we also find that concreteness facilitates prosocial behavior among people who highly value loyalty. These findings help resolve theoretical ambiguity about the cognitive underpinnings of prosociality, and they have important practical implications for optimal framing of charity appeals to potential donors.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23869"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565140","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}
引用次数: 0
Conditional autoregressive model based on next scale prediction for missing data reconstruction. 基于下一尺度预测的缺失数据重建条件自回归模型。
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-08830-5
Shuang Wang, Xiangpeng Wang, Yuhan Yang, Peifan Jiang, Bin Wang, Yuanhao Li
{"title":"Conditional autoregressive model based on next scale prediction for missing data reconstruction.","authors":"Shuang Wang, Xiangpeng Wang, Yuhan Yang, Peifan Jiang, Bin Wang, Yuanhao Li","doi":"10.1038/s41598-025-08830-5","DOIUrl":"https://doi.org/10.1038/s41598-025-08830-5","url":null,"abstract":"<p><p>Seismic data collected under complex field conditions often contain missing traces. Traditional theory-driven methods rely heavily on empirically selected parameters and struggle to reconstruct continuous missing traces effectively. With advancements in deep learning, various generative models have exhibited strong reconstruction capabilities. However, diffusion model-based methods face significant reconstruction time overhead due to their iterative sampling strategies. Existing transformer-based autoregressive methods flatten two-dimensional seismic data into one-dimensional sequences, disrupting the inherent two-dimensional structure and compromising the spatial locality of seismic information. To address these limitations, we propose a conditional autoregressive model based on next-scale prediction. Starting from the smallest scale, the model incrementally predicts larger-scale data using information from preceding smaller scales, ultimately achieving robust data reconstruction. This next-scale prediction approach avoids flattening the data, thereby preserving its spatial structure. Additionally, conditional constraints during autoregressive generation ensure that the predicted data at each scale remains consistent and aligns with the distribution of the known data. Reconstruction experiments on both field and synthetic datasets demonstrate that our method achieves superior reconstruction accuracy compared to existing approaches and effectively handles various complex missing data scenarios.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23904"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565145","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}
引用次数: 0
Assessment of the occurrence of adverse events through the global trigger tool in a university hospital in Italy. 通过全球触发工具评估意大利某大学医院不良事件发生情况。
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-08617-8
Vincenza Sansone, Giovanna Paduano, Maria Rosaria D'Emma, Maria Pavia
{"title":"Assessment of the occurrence of adverse events through the global trigger tool in a university hospital in Italy.","authors":"Vincenza Sansone, Giovanna Paduano, Maria Rosaria D'Emma, Maria Pavia","doi":"10.1038/s41598-025-08617-8","DOIUrl":"https://doi.org/10.1038/s41598-025-08617-8","url":null,"abstract":"<p><p>The reporting of adverse events (AEs) through incident reporting (IR) is considered a valuable tool to ensure their analysis. In addition, the Global Trigger Tool (GTT) methodologies allow a review of clinical records through triggers. The purposes of this study were to assess the occurrence, type and severity of AEs detected by the GTT, comparing the results with the IR system. A retrospective study was conducted between September and November 2023 in Italy on 500 clinical records of patients admitted in 2022 and 2023. A total of 59 AEs were detected in 45 patients (11.8%), and all were associated with at least one trigger. The most frequent AEs were healthcare-associated infections (HAI) (32.2%), medication (27.1%), procedures (23.7%), and healthcare-related AEs (17%). Only 3.4% of the AEs revealed by GTT were also reported in the IR system. Male sex, higher Charlson index, and length of stay were significantly associated with higher results of AE. Significant predictors of in-hospital death were permanence in intensive care units and exposure to central venous catheter. The GTT demonstrated to be feasible and to provide a broader evaluation of the pattern of AEs in the hospital. The findings suggest the need to rely on multiple data sources and methodologies to identify AEs.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23973"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565159","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}
引用次数: 0
Causal association between cathepsins and asthma: a Mendelian randomization study. 组织蛋白酶与哮喘的因果关系:一项孟德尔随机研究。
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-08457-6
Feng Qiu, Wei Shao, Xue Qin, Ran Xu, Yifan Liu, Hua Lu
{"title":"Causal association between cathepsins and asthma: a Mendelian randomization study.","authors":"Feng Qiu, Wei Shao, Xue Qin, Ran Xu, Yifan Liu, Hua Lu","doi":"10.1038/s41598-025-08457-6","DOIUrl":"https://doi.org/10.1038/s41598-025-08457-6","url":null,"abstract":"<p><p>Asthma, a chronic respiratory disease affecting millions worldwide, poses a significant public health burden. Cathepsins, a group of proteolytic enzymes, have recently been implicated in asthma pathophysiology, though their exact causal role remains unclear. To address this gap, we conducted univariate and multivariate Mendelian randomization (MR) analyses using data from the INTERVAL study (3301 European ancestry participants) and FinnGen consortium (46,684 asthma cases and 219,734 controls). Our analysis employed inverse variance weighting (IVW), median weighting, and MR-Egger regression to ensure robustness and explore causality from multiple perspectives. Sensitivity analyses were performed to assess heterogeneity and pleiotropy.Results indicated a significant association between elevated cathepsin L2 levels and increased asthma risk (OR  1.058, 95% CI 1.016-1.101, P = 0.006), suggesting a potential role of cathepsin L2 in asthma pathogenesis. No significant effect of asthma status on cathepsin L2 levels was observed (P = 0.550), ruling out reverse causality. Multivariable MR further confirmed the independent association of cathepsin L2 with asthma risk. Sensitivity analyses supported these findings with no evidence of significant pleiotropy.This study is the first to apply Mendelian randomization to explore the causal relationship between cathepsins and asthma, highlighting cathepsin L2 as a key player in asthma pathophysiology. These findings offer novel insights into asthma mechanisms and suggest cathepsin L2 as a potential therapeutic target warranting further investigation.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23984"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565167","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}
引用次数: 0
Intelligent brain tumor detection using hybrid finetuned deep transfer features and ensemble machine learning algorithms. 使用混合微调深度转移特征和集成机器学习算法的智能脑肿瘤检测。
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-08689-6
Rakesh Salakapuri, Panduranga Vital Terlapu, Kishore Raju Kalidindi, Ramesh Naidu Balaka, D Jayaram, T Ravikumar
{"title":"Intelligent brain tumor detection using hybrid finetuned deep transfer features and ensemble machine learning algorithms.","authors":"Rakesh Salakapuri, Panduranga Vital Terlapu, Kishore Raju Kalidindi, Ramesh Naidu Balaka, D Jayaram, T Ravikumar","doi":"10.1038/s41598-025-08689-6","DOIUrl":"https://doi.org/10.1038/s41598-025-08689-6","url":null,"abstract":"<p><p>Brain tumours (BTs) are severe neurological disorders. They affect more than 308,000 people each year worldwide. The mortality rate is over 251,000 deaths annually (IARC, 2020 reports). Detecting BTs is complex because they vary in nature. Early diagnosis is essential for better survival rates. The study presents a new system for detecting BTs. It combines deep (DL) learning and machine (ML) learning techniques. The system uses advanced models like Inception-V3, ResNet-50, and VGG-16 for feature extraction, and for dimensional reduction, it uses the PCA model. It also employs ensemble methods such as Stacking, k-NN, Gradient Boosting, AdaBoost, Multi-Layer Perceptron (MLP), and Support Vector Machines for classification and predicts the BTs using MRI scans. The MRI scans were resized to 224 × 224 pixels, and pixel intensities were normalized to a [0,1] scale. We apply the Gaussian filter for stability. We use the Keras Image Data Generator for image augmentation. It applied methods like zooming and ± 10% brightness adjustments. The dataset has 5,712 MRI scans. These scans are classified into four groups: Meningioma, No-Tumor, Glioma, and Pituitary. A tenfold cross-validation method helps check if the model is reliable. Deep transfer (TL) learning and ensemble ML models work well together. They showed excellent results in detecting BTs. The stacking ensemble model achieved the highest accuracy across all feature extraction methods, with ResNet-50 features reduced by PCA (500), producing an accuracy of 0.957, 95% CI: 0.948-0.966; AUC: 0.996, 95% CI: 0.989-0.998, significantly outperforming baselines (p < 0.01). Neural networks and gradient-boosting models also show strong performance. The stacking model is robust and reliable. This method is useful for medical applications. Future studies will focus on using multi-modal imaging. This will help improve diagnostic accuracy. The research improves early detection of brain tumors.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23899"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565177","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}
引用次数: 0
Investigation of the production and antifungal properties of nanocapsules containing chamomile essential oil. 洋甘菊精油纳米胶囊的制备及抑菌性能研究。
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-08802-9
Tianjiao Liu, Xinyao Qu, Mojiao Zhao, Dafang Zhang, Jianpeng Guo
{"title":"Investigation of the production and antifungal properties of nanocapsules containing chamomile essential oil.","authors":"Tianjiao Liu, Xinyao Qu, Mojiao Zhao, Dafang Zhang, Jianpeng Guo","doi":"10.1038/s41598-025-08802-9","DOIUrl":"https://doi.org/10.1038/s41598-025-08802-9","url":null,"abstract":"<p><p>Our study aims to investigate the production of nanocapsules containing chamomile essential oil and assess their antifungal properties. We have developed a technological process for producing nanocapsules, selected chamomile raw materials, extracted the essential oil, and conducted research on the antimicrobial activity of nanocapsules against four fungal cultures: Candida albicans CGMCC 2.538, Aspergillus fumigatus CGMCC 3.5925, Trichophyton rubrum CGMCC 3.3777 and Epidermophyton floccosum CGMCC 3.3722. Our research revealed significant antimicrobial activity of chamomile-containing nanocapsules against all tested fungi. The zones of fungal inhibition varied depending on the oil concentration and were statistically significant (P < 0.05). The obtained results hold practical significance for the development of antimicrobial agents based on plant oils in the treatment of fungal infections. Further research may focus on the molecular mechanisms of chamomile oil's action, clinical trials in humans, and the optimization of nanocapsule formulations. These steps may contribute to the development of more effective and targeted antimicrobial agents for combating fungal infections and improving patient health.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23981"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565180","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}
引用次数: 0
Evaluation of MCAM expression in correlation with clinicopathological parameters of gastric cancer. MCAM表达与胃癌临床病理参数的相关性研究。
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-08732-6
Anna Pryczynicz, Marcin Nizioł, Agnieszka Brzozowska, Justyna Dorf, Konrad Zaręba, Katarzyna Guzińska-Ustymowicz
{"title":"Evaluation of MCAM expression in correlation with clinicopathological parameters of gastric cancer.","authors":"Anna Pryczynicz, Marcin Nizioł, Agnieszka Brzozowska, Justyna Dorf, Konrad Zaręba, Katarzyna Guzińska-Ustymowicz","doi":"10.1038/s41598-025-08732-6","DOIUrl":"https://doi.org/10.1038/s41598-025-08732-6","url":null,"abstract":"<p><p>MCAM (Melanoma Cell Adhesion Molecule) is an adhesion protein belonging to the immunoglobulin superfamily, which was identified as a melanoma-specific protein. It is now clear that it can also be found in other types of neoplasms, e.g. in the carcinoma of the prostate, breast, ovary and stomach. MCAM plays a major pro-migratory role in the vascular system, promoting metastases. Therefore the study objective was to immunohistochemically evaluate MCAM expression in gastric cancer as well as to examine the correlation with chosen clinical-histopathological parameters. The study has shown that positive expression of MCAM was observed in cancer cells in 42.5% and in stromal cells in 33.3% of patients. The expression was more frequently seen in low desmoplasia tumors. The positive expression was also associated with higher grade of Helicobacter pylori infection. No correlation was noted with the overall survival rate. The expression of MCAM in stroma showed no correlation with clinical-histopathological parameters and patients' survival. The assessment of MCAM expression is not a useful marker to identify tumor stage nor it is a prognostic factor of gastric cancer. However, this protein may contribute to the process of desmoplastic stroma formation and be involved in the mechanism of inflammatory reaction.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23909"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565197","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}
引用次数: 0
Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis. 机器学习结合多组学鉴定免疫相关LncRNA信号作为预测乳腺癌预后的生物标志物
IF 3.8 2区 综合性期刊
Scientific Reports Pub Date : 2025-07-04 DOI: 10.1038/s41598-025-10186-9
Yuxing Liu, Jintao Chen, Daifeng Yang, Chenming Liu, Chunhui Tang, Shanshan Cai, Yingxuan Huang
{"title":"Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis.","authors":"Yuxing Liu, Jintao Chen, Daifeng Yang, Chenming Liu, Chunhui Tang, Shanshan Cai, Yingxuan Huang","doi":"10.1038/s41598-025-10186-9","DOIUrl":"https://doi.org/10.1038/s41598-025-10186-9","url":null,"abstract":"<p><p>This study developed an immune-related long non-coding RNAs (lncRNAs)-based prognostic signature by integrating multi-omics data and machine learning algorithms to predict survival and therapeutic responses in breast cancer patients. Utilizing transcriptomic and gene expression data from TCGA and GEO databases, 72 immune-related lncRNAs were identified through weighted gene co-expression network analysis (WGCNA) and ImmuLncRNA algorithms. The model was further optimized using 101 combinations of 10 machine learning approaches, ultimately constructing an immune-related lncRNA signature(IRLS) scoring system comprising nine key lncRNAs. Validated across 17 independent cohorts, the model demonstrated that high-risk patients had significantly shorter overall survival (OS) (P < 0.05), with predictive performance surpassing 95 published models (P < 0.05). Additionally, the IRLS score predicted responses to paclitaxel chemotherapy, and the low-risk group exhibited higher immune cell infiltration (P < 0.05), showing significant negative correlations with CD8A, PD-L1, tumor mutational burden (TMB), and neoantigen load (NAL). In immune checkpoint inhibitor (ICI) treatment cohorts, low IRLS scores were associated with improved response rates to atezolizumab. Our findings suggest that the IRLS model serves as a novel biomarker for prognostic stratification and personalized therapeutic decision-making in breast cancer.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"23863"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565209","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}
引用次数: 0
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