Search Results (5,145)

Background: Persistent liver pathology despite a sustained virologic response (SVR) to hepatitis C virus (HCV) therapy is a major clinical concern. This is particularly relevant for people with HIV (PWH) with HCV coinfection, a population prone to accelerated liver disease progression. This study aimed to characterize the plasma miRNA profile in PWH with cirrhosis one year after successful completion of HCV therapy, and to explore their relationship with metabolite alterations. Methods: This cross-sectional study enrolled 47 PWH who achieved HCV clearance with antiviral therapy. Using plasma samples collected approximately one year after completion of HCV therapy, participants were stratified into two groups based on liver stiffness measurement (LSM): compensated cirrhosis (n = 32, LSM ≥ 12.5 kPa) and non-cirrhosis (n = 15, LSM < 12.5 kPa). Plasma miRNAs and metabolites were determined using small RNA sequencing and untargeted capillary electrophoresis-mass spectrometry (CE-MS), respectively. Significantly differentially expressed (SDE) miRNAs were identified using generalized linear models (GLM) with a negative binomial distribution, and their correlation with metabolite levels was quantified using Spearman’s correlation. Results: In the cirrhosis group (n = 32), we identified a distinct signature of 15 SDE miRNAs (9 upregulated, 6 downregulated) compared to the non-cirrhotic group (n = 15), showing hsa-miR-10401-3p, hsa-miR-548ak, hsa-miR-141-3p, and hsa-miR-3940-3p the largest expression changes. miRNA-gene interaction and pathway enrichment analysis suggested that these 15 SDE miRNAs potentially regulate multiple genes involved in immune response and amino acid metabolism. In addition, correlation analyses with our metabolomic data revealed significant associations between specific SDE miRNAs and amino acids and their derivatives. Specifically, the expression of upregulated miRNAs (e.g., hsa-miR-10401-3p and hsa-miR-16-5p) was positively correlated with plasma levels of L-methionine and its derivatives, while downregulated miRNAs (e.g., hsa-miR-625-5p) were inversely correlated with L-tryptophan. Conclusions: In cirrhotic PWH with history of HCV coinfection, a distinct plasma miRNA signature linked to dysregulated amino acid metabolism is found one year after completion of HCV therapy. This underscores that the HCV cure does not equate to complete hepatic recovery, highlighting the critical need for long-term monitoring in this high-risk population. Full article

Influenza is typically framed as an acute respiratory infection, yet accumulating evidence suggests that—like SARS-CoV-2—it may trigger persistent, multi-organ morbidity consistent with a post-acute infection syndrome (“long flu”). Leveraging the nationwide FinnGen registry infrastructure, we conducted a temporally stratified disease-wide association study (DWAS) to map antecedent risk factors and long-term sequelae following clinically diagnosed influenza and COVID-19. We assembled an exposed cohort comprising 9204 individuals with influenza (ICD-10 J09–J11) and 4,258 individuals with COVID-19 (ICD-10 U072) recorded in specialist inpatient/outpatient care between 1998 and 2021, and an unexposed comparator cohort of 420,005 individuals with no recorded influenza or pneumonia (J09–J18) across their available medical history. Across harmonized clinical endpoints, we fitted age- and sex-adjusted Cox proportional hazards models and controlled for multiple testing using a stringent false discovery rate threshold (FDR-adjusted p<0.001), further interrogating temporal persistence within 1-, 5-, and 15-year windows. The DWAS revealed that both infections are associated with broad, system-spanning disease signatures extending beyond the respiratory tract, including circulatory, neurological, metabolic, musculoskeletal, digestive, mental/behavioural, ocular, and oncologic endpoints. Predisposition analyses demonstrated that infection risk is concentrated in individuals with substantial pre-existing multimorbidity, most prominently cardiovascular disease, alongside cardiometabolic, respiratory, renal, neuropsychiatric, and inflammatory conditions. Post-infection analyses identified a durable burden of incident multi-system morbidity after influenza, with particularly robust and persistent cardiovascular and neurological signatures—encompassing thromboembolic disease and major adverse cardiovascular outcomes, as well as migraine, neurodegenerative disorders, and depression—together with metabolic and renal sequelae that, in subsets, extended across multi-year horizons. Collectively, these longitudinal findings reframe influenza as a systemic event embedded within a chronic disease continuum, motivate recognition of “long flu” as a clinically meaningful post-viral risk landscape, and support intensified prevention and risk-stratified surveillance strategies alongside analogous efforts for long COVID. Full article

Personality traits are well-established predictors of safety behavior in construction, yet the cognitive mechanisms through which these traits influence such behavior remain poorly understood. In particular, hazard recognition and risk perception are underexamined cognitive mediators that elucidate how personality traits shape safety behavior. Moreover, the mediating effects of these cognitive processes are likely to vary across individuals, reflecting heterogeneity in background characteristics. Neglecting these mediating processes and their differentiated effects not only limits theoretical understanding of the pathways linking personality traits to safety behavior but also undermines the effectiveness of safety interventions. To address this gap, this study develops a framework incorporating cognitive mediators to examine how personality traits influence safety behavior (safety compliance and participation). The hypothesized cognitive-mediation pathways were tested using structural equation modeling based on offline questionnaire data collected from 213 site managers and workers. The findings reveal distinct cognitive pathways through which personality traits shape safety behavior. Extraversion and openness indirectly reduced safety compliance and safety participation by weakening hazard recognition and risk perception, either independently or sequentially. In contrast, agreeableness and conscientiousness enhanced safety behavior by strengthening these same cognitive processes. Higher education levels positively moderated certain mediating effects, whereas extensive work experience exerted mixed influences on specific pathways, facilitating some and inhibiting others depending on context. These findings deepen understanding of the internal mechanisms through which personality traits influence safety behavior via risk cognition. By identifying differentiated pathways across groups, this study further refines the theoretical framework explaining construction workers’ safety behavior. In addition, the theoretical insights generated by this study offer proactive and effective directions for safety practice, including improving person–job fit, designing targeted risk cognition training, and implementing stratified safety management strategies. Full article

Salmonella, a major global foodborne pathogen, is a leading cause of salmonellosis. Quantitative detection of Salmonella provides a scientific basis for establishing microbiological criteria and conducting risk assessments. The plate count method remains the primary approach for bacterial quantification, whereas the most probable number (MPN) method is commonly used for detecting low levels of bacterial contamination. However, both methods are time-consuming and labor-intensive. Validated digital polymerase chain reaction (dPCR) techniques are emerging as promising alternatives because they enable rapid, absolute quantification with high specificity and sensitivity. Herein, we developed a novel droplet dPCR (ddPCR) assay for identifying and quantifying Salmonella using invA as the target. The assay demonstrated high specificity and sensitivity, with a limit of quantification of 1.1 × 10² colony-forming units/mL in meat samples. Furthermore, the log₁₀ values obtained via ddPCR and plate counting exhibited a strong linear relationship (R² > 0.99). Mathematical modeling of growth kinetics further confirmed a high correlation between plate count and ddPCR measurements (Pearson correlation coefficient: 0.996; calculated bias factor: 0.88). Collectively, these results indicate that ddPCR is a viable alternative to the MPN method and represents a powerful tool for the quantitative risk assessment of food safety. Full article

Background: Nurses’ clinical reasoning is increasingly being recognized as a core competence that enhances the quality and safety of care across diverse healthcare settings. Nurses with refined clinical reasoning skills contribute significantly to improved health outcomes and broader health gains. In emergency departments, this competence is essential to rapidly assessing complex problems, anticipating complications, and preventing the deterioration of patients’ clinical conditions. Such expertise enables nurses to discern the severity of clinical situations quickly and intervene effectively. Objectives: The aims of this study were to analyze the clinical reasoning process of nurses and develop a theory that explains this process in emergency care settings. Methodology: This qualitative study explored the following research question: “How do nurses enact the clinical reasoning process in emergency departments?” The Grounded Theory methodology was used, with a theoretical sample of 20 nurses. Data collection methods included in-depth interviews, participant observation, and field notes. Results: The theoretical analysis identified clinical reasoning as a substantive theory composed of two subprocesses: Diagnostic Nursing Assessment and Therapeutic Nursing Intervention. Nurses’ clinical reasoning determines two levels of patient severity—Level I, life-threatening situations (immediate risk), and Level II, non-life-threatening situations (expressed problems)—according to which nursing interventions are adjusted. Conclusions: The Nursing Clinical Reasoning Model is a dynamic and continuous process that involves both Diagnostic Nursing Assessment and Nursing Therapeutic Intervention. It is deeply rooted in the nurse–patient–family relationship and is shaped by the specific care context, which influences nurses’ assessments and interventions and patients’ responses and behaviors. Full article

Chronic inflammation constitutes a well-established driver of colorectal carcinogenesis, yet the molecular circuitry linking inflammatory receptor signalling to tumour cell survival remains incompletely delineated. Here we demonstrate that the HMG-CoA reductase inhibitors atorvastatin and rosuvastatin modulate inflammatory survival pathways in colorectal cancer cells in a manner consistent with targeted interference with the protease-activated receptor 2 (PAR-2)–extracellular signal-regulated kinase (ERK)–tumour necrosis factor-α (TNF-α) signalling axis. Using lipopolysaccharide-stimulated HT-29 and Caco-2 cells as complementary models of inflammatory colorectal malignancy, we show that both statins selectively attenuate PAR-2 expression at the protein and transcript levels while leaving structurally related PAR-1 unaffected. This pattern of receptor modulation is accompanied by suppression of total ERK1/2 expression, ERK1/2 phosphorylation, and the transcriptional target DUSP6, together with attenuation of TNF-α secretion. Importantly, these signaling shifts are associated with dual apoptotic programs; the extrinsic pathway, reflected by transcriptional upregulation and proteolytic activation of caspase-8; and the intrinsic mitochondrial pathway, evidenced by reciprocal modulation of Bcl-2 family proteins favoring Bax over Bcl-2. Both pathways converge upon activation of executioner caspase-3 and an increase in Annexin V-defined apoptotic fractions, indicating re-engagement of programmed cell death under inflammatory stress. Notably, rosuvastatin consistently demonstrates superior potency across signaling endpoints, achieving comparable biological effects at lower concentrations than atorvastatin. Collectively, these data indicate that clinically deployed statins target the PAR-2–ERK axis and are associated with re-activation of apoptotic pathways in inflammatory colorectal cancer models, while leaving open the possibility that additional statin-responsive networks contribute to their pro-apoptotic effects. This mechanistic framework provides biological plausibility for epidemiologic observations linking statin use with reduced colorectal cancer risk and improved outcomes, and supports further translational evaluation of PAR-2-directed statin strategies in colorectal malignancy. Full article

The impacts of land use on stormwater runoff quality and Best Management Practices to mitigate these impacts have been investigated since the 1970s, yet challenges remain in providing a modeling approach that concomitantly considers contributions from different land use types. In densely developed urban areas, a buildup/washoff approach is often applied, while in rural areas, some type of erosion modeling is employed, as the processes of detachment, entrainment, and transport are fundamentally different. This study presents a coupled modeling approach within PCSWMM, integrating exponential buildup/washoff for impervious surfaces with the Modified Universal Soil Loss Equation (MUSLE) for pervious areas, including construction sites, to characterize water quality in the large mixed urban–rural Sparrovale catchment in Geelong, Australia. The watershed includes an innovative cascading system of 12 online NbS wetlands along one of the main tributaries, Armstrong Creek, to manage runoff quantity and quality, as well as 16 offline NbS wetlands that are tributary to the online system. A total of 78 samples for Total Suspended Solids (TSS), Total Phosphorus (TP), and Total Nitrogen (TN) were collected from six monitoring sites along Armstrong Creek during wet- and dry-weather events between May and July 2024 for model validation. The data were supplemented with six other catchment stormwater quality datasets collected during earlier studies, which provided an understanding of water quality status for the broader Geelong region. Results showed that average nutrient concentrations across all the sites ranged from 0.44 to 2.66 mg/L for TP and 0.69 to 5.7 mg/L for TN, spanning from within to above the ecological threshold ranges for eutrophication risk (TP: 0.042 to 1 mg/L, TN: 0.3 to 1.5 mg/L). In the study catchment, upstream wetlands reduced pollutant levels; however, downstream wetlands that received runoff from agriculture, residential areas, and, importantly, construction sites, showed a substantial increase in sediment and nutrient concentration. Water quality modeling revealed washoff parameters primarily influenced concentrations from established urban neighborhoods, whereas erosion parameters substantially impacted total pollutant loads for the larger system, demonstrating the importance of integrated modeling for capturing pollutant dynamics in heterogeneous, urbanizing catchments. The study results emphasize the need for spatially targeted management strategies to improve stormwater runoff quality and also show the potential for cascading wetlands to be an important element of the Nature-based Solution (NbS) runoff management system. Full article

Background/Objectives: Type 2 diabetes (T2D) is a chronic metabolic disorder closely linked to cardiovascular disease and obesity and notably influenced by lifestyle and dietary patterns. The Mediterranean diet has well-established benefits across multiple cardiometabolic risk factors, including those relevant to diabetes. This study aimed to investigate the degree to which adults with T2D adhere to a Mediterranean dietary pattern and to examine how such adherence relates to glycemic and lipidemic regulation. Methods: This cross-sectional study included 100 adults with T2D (54 men and 46 women). Adherence to the Mediterranean diet was assessed using the Mediterranean Diet Score (MDS). Demographic, anthropometric, lifestyle, and clinical data were collected, and glycemic and lipid parameters were analyzed. Associations between Mediterranean diet adherence and metabolic outcomes were examined using correlation analyses and multivariable regression models adjusted for relevant confounders. Results: Most participants showed low adherence to the Mediterranean diet. A significant inverse association was observed between Mediterranean diet adherence and hemoglobin A1c (HbA1c) levels, with individuals scoring ≤35 on the MDS demonstrating higher HbA1c levels. Similar trends were observed in the lowest tertile of adherence. Notably, each one-point increase in MDS predicted a 0.13% reduction in HbA1c. In multivariable regression analyses, Mediterranean diet adherence remained the strongest predictor of glycemic control, independent of age, body mass index (BMI), sex, smoking status, physical activity and the number of antidiabetic treatments. Higher adherence was also significantly associated with lower low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) levels, as well as higher high-density lipoprotein cholesterol (HDL) concentrations. Conclusions: Greater adherence to the Mediterranean diet is independently associated with improved glycemic regulation and a more favorable lipid profile in adults with T2D. These findings support the Mediterranean diet as a valuable non-pharmacologic strategy for optimizing metabolic outcomes in people with T2D. Full article

Background: Libya, a conflict-affected North African country, has a fragile health system and poor surveillance, leaving it largely underrepresented in global estimates. Earlier Libyan reviews were descriptive, lacking breakpoint standardization, isolate-level pooling, or AMR-attributable mortality and DALY estimates. To our knowledge, this study represents the first comprehensive report that integrates phenotypic and genotypic data to estimate deaths and DALYs attributable to AMR-induced mortality and morbidity, describe spatiotemporal patterns, and model future trajectories. Methods: We performed a meta-analysis according to the PRISMA 2020 guideline of Libyan studies reporting phenotypic or genotypic resistance among clinical bacterial isolates (1970–2024), combined with microbiology records from hospitals and national surveillance systems (preregistered in PROSPERO ID: CRD420251066018). Susceptibility results were standardized to CLSI/EUCAST and deduplicated using WHO GLASS first-isolate rules. We used random-effects meta-regression to estimate pooled resistance, and the counterfactual approach of Global Burden of Disease (GBD) was applied to estimate AMR-attributable DALYs. Molecular data on resistance genes, sequence types, and tuberculosis mutations were systematically collected. Results: We included 62 eligible studies together with national and facility-level surveillance datasets, providing isolate-level susceptibility data for 31,439 clinical isolates from Libya. In 2024, we estimated 2183 deaths (95% UI 1752–2614) attributable to AMR, representing 9.7% (95% UI 7.8–11.6) of total deaths with a mortality rate of 15.2 per 100,000 (12.2–18.2). DALYs attributable to AMR increased from 14,628 (95% UI 11,702–17,554) in 1970 to 96,715 (95% UI 77,372–116,058). The highest pooled resistance involved carbapenem-resistant/MDR A. baumannii, third-generation cephalosporin- and fluoroquinolone-resistant Enterobacterales, and carbapenem-resistant P. aeruginosa. Molecular data showed widespread ESBLs, OXA-/NDM-type carbapenemases, plasmid-mediated colistin resistance, high-risk E. coli ST131 and K. pneumoniae ST147 lineages, and canonical drug-resistant M. tuberculosis mutations. Conclusions: Combined with global and regional evidence, our findings suggest a high and increasing burden of AMR in Libya. These findings emphasize the need for rapid expansion of data collection systems, GLASS-aligned surveillance, diagnostic capacities, and infection control measures. Full article

Low social status leads to chronic social stress that predicts risk for physical and mental illness, especially when it starts early in life. To examine the longitudinal effects of low social status on the immune system, this study assessed the effects of low social status on developmental secretory patterns of pro- and anti-inflammatory markers under baseline conditions, as well as in response to an immune challenge (lipopolysaccharide (LPS)-induced activation of pro- and anti-inflammatory cytokines) in a translational rhesus monkey model of lifelong social subordination stress. Baseline blood samples were collected in 27 socially housed female rhesus monkeys (13 dominants, DOM, and 14 subordinates, SUB) during infancy (6 months), the juvenile pre-pubertal period (16 months), and adulthood (9–10 years) to examine the longitudinal effects of social status on inflammatory markers in unstimulated versus LPS-stimulated conditions mimicking exposure to bacterial infection. Basal levels of the stress hormone cortisol in blood were measured to examine associations between inflammation and activity of the hypothalamic–pituitary–adrenal (HPA) axis throughout the life span. Basal peripheral levels of inflammatory markers (e.g., IL-6) increased across development in both SUB and DOM animals with no significant differences. Basal cortisol levels were significantly higher in infancy as compared to adulthood, but no significant effects of social rank were detected. However, in adulthood, SUB animals showed a cytokine-specific immune response to ex vivo LPS stimulation with significantly higher secretions of IL-1β, IL-2, and IL-10 compared to DOM animals, whereas IL-8 response to LPS was lower in SUB animals than in DOMs. This cytokine-specific response to an immune challenge that mimics bacterial infection could reflect dysregulated immune cells that may have short-term adaptation, but at the cost of longer-term risks for low-grade chronic inflammation and accelerated immune aging for socially subordinate female macaques. Full article

Introduction: The COVID-19 pandemic had significant effects on mental health and lifestyle behaviours, especially among university students who experienced academic disruptions, social isolation, and fewer social interactions. Alcohol consumption has long been part of student culture. Still, the influence of post-pandemic academic reintegration on drinking patterns and psychological distress remains relatively unexplored, particularly in countries like Portugal, where student traditions heavily shape consumption habits. This study aimed to describe the prevalence of alcohol consumption, depression, anxiety, and stress in a sample of Portuguese university students during the post-pandemic academic period, and to explore associations with sociodemographic variables. Methods: A cross-sectional study was conducted in November 2021 with 90 students from a private higher education institution in northern Portugal. Data were collected via an online questionnaire including sociodemographic information, the Alcohol Use Disorders Identification Test (AUDIT), and the Depression, Anxiety and Stress Scale (DASS-21). Result: The majority of the participants were not at risk of alcohol addiction (95.3%). In total, 15.1% of students reported anxiety symptoms ranging from severe to extremely severe. A binomial logistic regression was performed to ascertain the effects of being away from home and psychological distress (DASS-42 score), on the likelihood that participants were at risk of alcohol addiction (Level 3 and 4 in the AUDIT scale). The logistic regression model was statistically significant, χ²(2) = 9.20, p = 0.010. Living away from home was associated with a substantially lower likelihood of high-risk status (B = −2.79, p = 0.034), corresponding to an odds ratio of 0.06, indicating a strong protective effect. DASS-42 total score was positively associated with high-risk status (B = 0.04, p = 0.039), such that higher psychological distress increased the odds of being classified as high risk. Conclusions: The findings reveal a low prevalence of alcohol risk but heightened symptoms of anxiety, depression, and stress. Psychological distress notably increases the likelihood of hazardous alcohol use, emphasising the importance of targeted mental health and alcohol-use interventions among university students. Full article

Copper contamination in aquatic environments poses significant ecological and health risks, necessitating efficient and resilient treatment strategies. In this study, graphene oxide (GO) and magnetic graphene oxide (MGO) were synthesized and comprehensively evaluated for Cu(II) removal using an integrated multivariate approach combining kinetic and isotherm modelling, Response Surface Methodology (RSM), and advanced statistical analyses. Both adsorbents achieved high removal efficiencies (>90%) under optimized conditions, with Langmuir capacities of 59.2 mg g⁻¹ for GO and 40.1 mg g⁻¹ for MGO. Kinetic modelling confirmed reaction-controlled adsorption, while Freundlich isotherms highlighted heterogeneous surface binding. RSM identified pH as the dominant factor governing removal efficiency, with significant interactions among pH, Cu(II), and DOC reflecting competitive matrix effects. Principal Component Analysis (PCA) revealed that GO performance is strongly influenced by solution chemistry, whereas MGO exhibits reduced sensitivity due to modified physicochemical properties. FTIR analysis confirmed that adsorption proceeds primarily through electrostatic attraction and inner-sphere complexation, with Fe–O sites contributing to MGO’s enhanced affinity. Regeneration studies demonstrated superior reusability of MGO, which retained ~64% efficiency after five cycles compared to ~52% for GO. Collectively, these multivariate and mechanistic insights identify MGO as a more robust, versatile, and regenerable sorbent for Cu(II) removal under realistic water-matrix conditions. Full article

This study investigates the factors influencing Chinese K-12 teachers’ adoption of generative artificial intelligence (GenAI) for instructional purposes by extending the Technology Acceptance Model (TAM) with pedagogical beliefs, perceived intelligence, perceived ethical risks, GenAI anxiety, and demographic moderators. Drawing on a theory-driven framework, survey data were collected from 218 in-service teachers across K-12 schools in China. The respondents were predominantly from urban schools and most had prior GenAI use experience. Eight latent constructs and fourteen hypotheses were tested using structural equation modeling and multi-group analysis. Results show that perceived usefulness and perceived ease of use are the strongest predictors of teachers’ intention to adopt GenAI. Constructivist pedagogical beliefs positively predict both perceived usefulness and intention, whereas transmissive beliefs negatively predict intention. Perceived intelligence exerts strong positive effects on perceived usefulness and ease of use but has no direct effect on intention. Perceived ethical risks significantly heighten GenAI anxiety, yet neither directly reduces adoption intention. Gender, teaching stage, and educational background further moderate key relationships, revealing heterogeneous adoption mechanisms across teacher subgroups. The study extends TAM for the GenAI era and highlights the need for professional development and policy initiatives that simultaneously strengthen perceived usefulness and ease of use, engage with pedagogical beliefs, and address ethical and emotional concerns in context-sensitive ways. Full article

Background: A sedentary lifestyle contributes to chronic disease risk in adults and may predict unfavourable body composition in adolescents. Declining physical activity and rising sedentary behaviour are linked to increasing global obesity rates. Given the scarcity of longitudinal studies examining how participation in organized sports and screen device use relate to body composition in early adolescence, this study aims to address this gap by analyzing temporal trends in both sexes. Methods: A sample of 158 Italian students, 38% of whom were female, was followed longitudinally from ages 11 to 13. Annual anthropometric assessments were conducted, and self-reported data on screen time and organised sports participation were collected. Fat mass (FM), fat-free mass (FFM), fat mass index (FMI), fat-free mass index (FFMI), body mass index (BMI), and waist-to-height ratio (WHtR) were subsequently calculated, along with annual increments. Repeated-measures ANOVA assessed age and sex effects, while multiple regression models evaluated associations between behavioural variables or sex and body composition indices. Results: Significant differences in %F, FM, FFM and its increment, WHtR and its increment, FMI, and FFMI (all p < 0.01) were observed by age and sex interaction. At age 13, weekly sports participation was negatively associated with annual increments in %F (β = −0.204, p = 0.04) and FMI (β = −0.227, p = 0.03). Female sex was associated with greater increments in %F (β = 0.188, p < 0.05) and WHtR (β = 0.323, p < 0.01), and with smaller increments in FFM (β = −0.421, p < 0.01). No significant associations were found for screen time (p > 0.05). Conclusions: Sporting during early adolescence seems to have positive effects on body composition changes, while sex-specific patterns warrant further attention. A deeper understanding of how early adolescent lifestyle factors, such as physical activity and sedentary behaviour, shape body composition is essential for promoting long-term health. Full article

Due to the unpredictability of seismic and the complexity of collection environments, significant uncertainty exists regarding their impact on cultural relics. Moreover, existing research on the causal analysis of seismic damage to cultural relics remains insufficient, thereby limiting advancements in risk assessment and protective measures. To address this issue, this paper proposes a seismic damage risk assessment method for cultural relics in collections, integrating deep learning and reinforcement strategies. The proposed method enhances the dataset on seismic impacts on cultural relics by developing an integrated deep learning-based data correction model. Furthermore, it incorporates a graph attention mechanism to precisely quantify the influence of various attribute factors on cultural relic damage. Additionally, by combining reinforcement learning with the Deep Deterministic Policy Gradient (DDPG) strategy, this method refines seismic risk assessments and formulates more targeted preventive protection measures for cultural relics in collections. This study evaluates the proposed method using three public datasets in comparison with the self-constructed Seismic Damage Dataset of Cultural Relics (CR-SDD). Experiments are conducted to assess and analyze the predictive performance of various models. Experimental results demonstrate that the proposed method achieves an accuracy of 81.21% in assessing seismic damage to cultural relics in collections. This research provides a scientific foundation and practical guidance for the protection of cultural relics, offering strong support for preventive conservation efforts in seismic risk mitigation. Full article