Integration of electronic nose, electronic tongue, and colorimeter in combination with chemometrics for monitoring the fermentation process of Tremella fuciformis.

This study proposes an efficient method for monitoring the submerged fermentation process of Tremella fuciformis (T. fuciformis) by integrating electronic nose (e-nose), electronic tongue (e-tongue), and colorimeter sensors using a data fusion strategy. Chemometrics was employed to establish qualitative identification and quantitative prediction models. The Pearson correlation analysis was applied to extract features from the e-nose and tongue sensor arrays. The optimal sensor arrays for monitoring the submerged fermentation process of T. fuciformis were obtained, and four different data fusion methods were developed by incorporating the colorimeter data features. To achieve qualitative identification, the physicochemical data and principal component analysis (PCA) results were utilized to determine three stages of the fermentation process. The fusion signal based on full features proved to be the optimal data fusion method, exhibiting the highest accuracy across different models. Notably, random forest (RF) was shown to be the most accurate pattern recognition method in this paper. For quantitative prediction, partial least squares regression (PLSR) and support vector regression (SVR) were employed to predict the sugar content and dry cell weight during fermentation. The best respective predictive R2 values for reducing sugar, tremella polysaccharide and dry cell weight were found to be 0.965, 0.988, and 0.970. Furthermore, due to its ability to capture nonlinear data relationships, SVR had superior performance in prediction modeling than PLSR. The results demonstrated that the combination of electronic sensor fusion signals and chemometrics provided a promising method for effectively monitoring T. fuciformis fermentation.

Long-term exposure to ambient ozone and adult-onset asthma: A prospective cohort study.

BACKGROUND: The association between long-term exposure to ozone (O3) and adult-onset asthma (AOA) remains inconclusive, and analysis of causality is lacking. OBJECTIVES: To examine the causal association between long-term O3 exposure and AOA. METHODS: A prospective cohort study of 362,098 participants was conducted using the UK Biobank study. Incident cases of AOA were identified using health administrative data of the National Health Services. O3 exposure at participants' residential addresses was estimated by a spatio-temporal model. Instrumental variable (IV) modelling was used to analyze the causal association between O3 exposure and AOA, by incorporating wind speed and planetary boundary layer height as IVs into time-dependent Cox model. Negative control outcome (accidental injury) was also used to additionally evaluate unmeasured confounding. RESULTS: During a mean follow-up of 11.38 years, a total of 10,973 incident AOA cases were identified. A U-shaped concentration-response relationship was observed between O3 exposure and AOA in the traditional Cox models with HR of 0.917 (95% CI: 0.889, 0.946) for O3 at low levels (<38.17 ppb), and 1.198 (95% CI: 1.162, 1.236) for O3 at high levels (≥38.17 ppb). However, in the IV analysis we only found a statistically significant association between high-level O3 exposure and AOA risk, but not for low-level O3 exposure. No significant associations between O3 exposure and accidental injury were observed. CONCLUSION: Our findings suggest a potential causal relationship between long-term exposure to high-level ambient O3 and increased risks of AOA.

Open and closed microfluidics for biosensing.

Biosensing is vital for many areas like disease diagnosis, infectious disease prevention, and point-of-care monitoring. Microfluidics has been evidenced to be a powerful tool for biosensing via integrating biological detection processes into a palm-size chip. Based on the chip structure, microfluidics has two subdivision types: open microfluidics and closed microfluidics, whose operation methods would be diverse. In this review, we summarize fundamentals, liquid control methods, and applications of open and closed microfluidics separately, point out the bottlenecks, and propose potential directions of microfluidics-based biosensing.

De Novo Design of Spiro-Type Hole-Transporting Material: Anisotropic Regulation Toward Efficient and Stable Perovskite Solar Cells.

2,2',7,7'-Tetrakis(N,N-di-p-methoxyphenyl)-amine-9,9'-spirobifluorene (Spiro-OMeTAD) represents the state-of-the-art hole-transporting material (HTM) in n-i-p perovskite solar cells (PSCs). However, its susceptibility to stability issues has been a long-standing concern. In this study, we embark on a comprehensive exploration of the untapped potential within the family of spiro-type HTMs using an innovative anisotropic regulation strategy. Diverging from conventional approaches that can only modify spirobifluorene with single functional group, this approach allows us to independently tailor the two orthogonal components of the spiro-skeleton at the molecular level. The newly designed HTM, SF-MPA-MCz, features enhanced thermal stability, precise energy level alignment, superior film morphology, and optimized interfacial properties when compared to Spiro-OMeTAD, which contribute to a remarkable power conversion efficiency (PCE) of 24.53% for PSCs employing SF-MPA-MCz with substantially improved thermal stability and operational stability. Note that the optimal concentration for SF-MPA-MCz solution is only 30 mg/ml, significantly lower than Spiro-OMeTAD (>70 mg/ml), which could remarkably reduce the cost especially for large-area processing in future commercialization. This work presents a promising avenue for the versatile design of multifunctional HTMs, offering a blueprint for achieving efficient and stable PSCs.

Impact of preoperative antiviral therapy on the prognosis of hepatitis B virus-related hepatocellular carcinoma.

BACKGROUND: For chronic hepatitis B virus (HBV) infection patients, increasing evidence has demonstrated the effectiveness of expanding the indications and applicable population for antiviral therapy. However, the expanded indication of antiviral therapy for hepatocellular carcinoma (HCC) remains to be further explored. METHODS: 196 HBV-related HCC patients who received radical hepatectomy and nucleos(t)ide analogues (NAs) therapy at Sichuan Provincial People's Hospital were enrolled in this study. HCC recurrence, overall survival (OS), early virological (VR) and biochemical responses (BR) of patients were compared between different NAs therapy and the use of anti-programmed cell death protein 1 (PD-1) therapy. RESULTS: NAs therapy at different timing of surgery was a strong independent risk factor for postoperative recurrence and overall mortality of HBV-related HCC patients. Furthermore, in HCC patients who received postoperative anti-PD-1 therapy, patients with HBV DNA < 1000 copy/mL had significantly better recurrence-free survival (RFS) and OS than those with HBV DNA ≥ 1000 copy/mL (HR: 7.783; P = 0.002; HR: 6.699; P < 0.001). However, the differences of RFS and OS rates between entecavir group and tenofovir disoproxil fumarate group were not statistically significant. Similar results were also observed in the rates of early VR, BR and combined VR and BR. CONCLUSION: Timely and reasonable preoperative NAs therapy showed clinical benefit in improving the prognosis of patients with HBV-related HCC, even in the case of normal alanine aminotransferase (ALT) level and negative hepatitis e antigen (HBeAg). Furthermore, a possible synergistic effect between antiviral therapy and anti-PD-1 therapy was founded and need further verification.

Air pollution, APOE genotype and risk of dementia among individuals with cardiovascular diseases: A population-based longitudinal study.

Individuals with cardiovascular disease (CVD) are particularly vulnerable to dementia, but it remains unclear whether air pollution exposure links with higher risk of dementia among those with CVD. The data were derived from the UK Biobank study (UKB). Dementia-free participants with CVD at baseline were included. Air pollution exposure was assessed through land use regression models, including particulate matter (PM2.5, PM2.5-10, and PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOX). A Cox proportional hazards model was used to investigate the associations between air pollution exposure and incident dementia among individuals with CVD. Air pollution was associated with dementia among individuals with CVD, and the hazard ratios of dementia associated with each interquartile range (IQR) µg/m3 increase in air pollution were 1.07 (95% CI: 1.02, 1.12) for PM2.5, 1.10 (95% CI: 1.04, 1.15) for PM10, 1.08 (95% CI: 1.03, 1.14) for NO2 and 1.05 (95% CI: 1.00, 1.09) for NOx. Associations between air pollution and all-cause dementia were found to be significant among individuals with hypertension. Adverse effects of air pollution were also observed for Alzheimer's dementia (AD) and vascular dementia (VaD), with a higher effect for AD. Observed associations remained similar in subgroups of APOE ε4 carriers and noncarriers, although there was a higher risk difference across different air pollution concentration among these individuals carrying APOE ε4. Air pollution emerges as a critical risk factor for dementia among individuals with CVD, regardless of genetic susceptibility indicated by the APOE genotype. Notably, individuals with hypertension might be susceptible to the adverse effects of air pollution, leading to a higher incidence of dementia. Understanding these impacts on dementia among individuals with CVD may promote better targeted prevention and clinical management strategies.

Causal association between long-term exposure to air pollution and incident Parkinson's disease.

Epidemiological evidence for long-term air pollution exposure and Parkinson's disease (PD) is controversial, and analysis of causality is limited. We identified 293,888 participants who were free of PD at baseline in the UK Biobank (2006-2010). Time-varying air pollution [fine particulate (PM2.5) and ozone (O3)] exposures were estimated using spatio-temporal models. Incident cases of PD were identified using validated algorithms. Four methods were used to investigate the associations between air pollution and PD, including (1) standard time-varying Cox proportional-hazard model; (2) Cox models weighted by generalized propensity score (GPS) and inverse-probability weights (IPW); (3) instrumental variable (IV) analysis; and (4) negative control outcome analysis. During a median of 11.6 years of follow-up, 1822 incident PD cases were identified. Based on standard Cox regression, the hazard ratios (95% confidence interval) for a 1 µg/m3 or ppb increase in PM2.5 and O3 were 1.23 (1.17, 1.30) and 1.02 (0.98, 1.05), respectively. Consistent results were found in models weighted by GPS and IPW, and in IV analysis. There were no significant associations between air pollution and negative control outcomes. This study provides evidence to support a causal association between PM2.5 exposure and PD. Mitigation of air pollution could be a protective measure against PD.

Fluorinated Polyimide Tunneling Layer for Efficient and Stable Perovskite Photovoltaics.

Despite the remarkable progress of perovskite solar cells (PSCs), challenges remain in terms of finding effective and viable strategies to enhance their long-term stability while maintaining high efficiency. In this study, a new insulating and hydrophobic fluorinated polyimide (FPI: 6FDA-6FAPB) was used as the interface layer between the perovskite layer and the hole transport layer (HTL) in PSCs. The functional groups of FPI play a pivotal role in passivating interface defects within the device. Due to its high work function, FPI demonstrates field-effect passivation (FEP) capabilities as an interface layer, effectively mitigating non-radiative recombination at the interface. Notably, the FPI insulating interface layer does not impede carrier transmission at the interface, which is attributed to the presence of hole tunneling effects. The optimized PSCs achieve an outstanding power conversion efficiency (PCE) of 24.61 % and demonstrate excellent stability, showcasing the efficacy of FPI in enhancing device performance and reliability.

Understanding Melt Pool Behavior of 316L Stainless Steel in Laser Powder Bed Fusion Additive Manufacturing.

In the laser powder bed fusion additive manufacturing process, the quality of fabrications is intricately tied to the laser-matter interaction, specifically the formation of the melt pool. This study experimentally examined the intricacies of melt pool characteristics and surface topography across diverse laser powers and speeds via single-track laser scanning on a bare plate and powder bed for 316L stainless steel. The results reveal that the presence of a powder layer amplifies melt pool instability and worsens irregularities due to increased laser absorption and the introduction of uneven mass from the powder. To provide a comprehensive understanding of melt pool dynamics, a high-fidelity computational model encompassing fluid dynamics, heat transfer, vaporization, and solidification was developed. It was validated against the measured melt pool dimensions and morphology, effectively predicting conduction and keyholing modes with irregular surface features. Particularly, the model explained the forming mechanisms of a defective morphology, termed swell-undercut, at high power and speed conditions, detailing the roles of recoil pressure and liquid refilling. As an application, multiple-track simulations replicate the surface features on cubic samples under two distinct process conditions, showcasing the potential of the laser-matter interaction model for process optimization.

A label-free strategy for immobilization of GPCRs using site-specific encoded non-natural amino acids to develop a selectively chromatographic approach for pursuing potential ligands binding to 5-hydroxytryptamine 1A receptor.

G protein-coupled receptors (GPCRs) are one of the most prominent targets for drug discovery. Immobilizing GPCRs has proven to be an effective strategy for expanding the utility of GPCRs into nonbiological contexts. However, traditional strategies of immobilizing GPCRs have been severely challenged due to the loss of receptor function. Here, we reported a novel and general approach to realize the label-free and site-selective immobilization of 5-hydroxytryptamine 1A receptor (5-HT1AR) and the application in developing a chromatographic method with improved specificity for pursuing 5-HT1AR ligands from natural products. This method involved the use of a clickable non-natural amino acid, O-allyl-L-tyrosine (O-ALTyr) to immobilize the receptor onto thiol-functionalized silica gels through a 'thiol-ene' click chemistry, which allowed us to avoid the purification step and directly immobilize 5-HT1AR on silica gels. The immobilized receptor was characterized using immunofluorescence assay, and receptor-ligand interaction analysis was conducted through frontal analysis. To test the feasibility of the immobilized 5-HT1ARO-ALTyr in complex matrices, bioactive compounds in Ziziphi Spinosae Semen (ZSS) were screened and their interaction with the receptor was assessed using zonal elution. Our findings indicated that immobilizing the receptor through nnAAs effectively minimizes the chromatographic peak tailing and broadening of specific ligands, leading to a significant improvement in chromatographic performance. The association constants of the three ligands to 5-HT1AR were approximately one order of magnitude greater than those of Halo-tag attachment. These results demonstrated that the immobilized 5-HT1AR exhibits high specificity and the ability to recognize receptor ligands from complex matrices. This allowed us to identify magnoflorine (Mag) as a potential ligand of 5-HT1AR from ZSS extract. In vivo assay also proved that Mag presented a promising anxiolytic effect by promoting the expression of 5-HT1AR in mice brain. The above findings pointed to the fact that the immobilized 5-HT1AR affinity chromatographic strategy relying on the site-specific encoded non-natural amino acid is a powerful alternative for precisely determining the drug-protein interaction and discovering the specific ligand of GPCRs from complex matrixes.

Advance typing of Vibrio parahaemolyticus through the mtlA and aer gene: A high-resolution, cost-effective approach.

Vibrio parahaemolyticus is a significant cause of foodborne illness, and its incidence worldwide is on the rise. It is thus imperative to develop a straightforward and efficient method for typing strains of this pathogen. In this study, we conducted a pangenome analysis of 75 complete genomes of V. parahaemolyticus and identified the core gene mtlA with the highest degree of variation, which distinguished 44 strains and outperformed traditional seven-gene-based MLST when combined with aer, another core gene with high degree of variation. The mtlA gene had higher resolution to type strains with a close relationship compared to the traditional MLST genes in the phylogenetic tree built by core genomes. Strong positive selection was also detected in the gene mtlA (ω > 1), representing adaptive and evolution in response to the environment. Therefore, the panel of gene mtlA and aer may serve as a tool for the typing of V. parahaemolyticus, potentially contributing to the prevention and control of this foodborne disease.

PSAC-6mA: 6mA site identifier using self-attention capsule network based on sequence-positioning.

DNA N6-methyladenine (6mA) modifications play a pivotal role in the regulation of growth, development, and diseases in organisms. As a significant epigenetic marker, 6mA modifications extensively participate in the intricate regulatory networks of the genome. Hence, gaining a profound understanding of how 6mA is intricately involved in these biological processes is imperative for deciphering the gene regulatory networks within organisms. In this study, we propose PSAC-6mA (Position-self-attention Capsule-6mA), a sequence-location-based self-attention capsule network. The positional layer in the model enables positional relationship extraction and independent parameter setting for each base position, avoiding parameter sharing inherent in convolutional approaches. Simultaneously, the self-attention capsule network enhances dimensionality, capturing correlation information between capsules and achieving exceptional results in feature extraction across multiple spatial dimensions within the model. Experimental results demonstrate the superior performance of PSAC-6mA in recognizing 6mA motifs across various species.

Utilization trend of prebiopsy multiparametric magnetic resonance imaging and its impact on prostate cancer detection: Real-world insights from a high-volume center in southwest China.

BACKGROUND: Data on the utilization and effects of prebiopsy prostate multiparametric magnetic resonance imaging (mpMRI) to support its routine use in real-world setting are still scarce. OBJECTIVE: To evaluate the change of clinical practice of prebiopsy mpMRI over time, and assess its diagnostic accuracy. DESIGN, SETTING, AND PARTICIPANTS: We retrospectively analyzed data from 6168 patients who underwent primary prostate biopsy (PBx) between January 2011 and December 2021 and had prostate-specific antigen (PSA) values ranging from 3 to 100 ng/mL. INTERVENTION: Prebiopsy MRI at the time of PBx. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We performed general linear regression and to elucidate trends in the annual use of prebiopsy mpMRI and conducted multivariable logistic regression to evaluate the potential benefits of incorporating prebiopsy mpMRI for prostate cancer (PCa) detection. RESULTS AND LIMITATIONS: The utilization of prebiopsy mpMRI significantly increased from 9.2% in 2011 to 75.0% in 2021 (p < 0.001). In addition, prebiopsy mpMRI significantly reduced negative PBx by 8.6% while improving the detection of clinically significant PCa (csPCa) by 7.0%. Regression analysis showed that the utilization of prebiopsy mpMRI was significantly associated with a 48% (95% confidence interval [CI]: 1.19-1.84) and 36% (95% CI: 1.12-1.66) increased PCa detection rate in the PSA 3-10 ng/mL and 10-20 ng/mL groups, respectively; and a 34% increased csPCa detection rate in the PSA 10-20 ng/mL group (95% CI: 1.09-1.64). The retrospective design and the single center cohort constituted the limitations of this study. CONCLUSIONS: Our study demonstrated a notable rise in the utilization of prebiopsy mpMRI in the past decade. The adoption of this imaging technique was significantly associated with an increased probability of detecting prostate cancer. PATIENT SUMMARY: From 2011 to 2021, we demonstrated a steady increase in the utilization of prebiopsy mpMRI among biopsy-naïve men. We also confirmed the positive impact of prebiopsy mpMRI utilization on the detection of prostate cancer.

Machine learning-based prediction model for distant metastasis of breast cancer.

BACKGROUND: Breast cancer is the most prevalent malignancy in women. Advanced breast cancer can develop distant metastases, posing a severe threat to the life of patients. Because the clinical warning signs of distant metastasis are manifested in the late stage of the disease, there is a need for better methods of predicting metastasis. METHODS: First, we screened breast cancer distant metastasis target genes by performing difference analysis and weighted gene co-expression network analysis (WGCNA) on the selected datasets, and performed analyses such as GO enrichment analysis on these target genes. Secondly, we screened breast cancer distant metastasis target genes by LASSO regression analysis and performed correlation analysis and other analyses on these biomarkers. Finally, we constructed several breast cancer distant metastasis prediction models based on Logistic Regression (LR) model, Random Forest (RF) model, Support Vector Machine (SVM) model, Gradient Boosting Decision Tree (GBDT) model and eXtreme Gradient Boosting (XGBoost) model, and selected the optimal model from them. RESULTS: Several 21-gene breast cancer distant metastasis prediction models were constructed, with the best performance of the model constructed based on the random forest model. This model accurately predicted the emergence of distant metastases from breast cancer, with an accuracy of 93.6 %, an F1-score of 88.9 % and an AUC value of 91.3 % on the validation set. CONCLUSION: Our findings have the potential to be translated into a point-of-care prognostic analysis to reduce breast cancer mortality.

Targeting Erbin-mitochondria axis in platelets/megakaryocytes promotes B cell-mediated antitumor immunity.

The roles of platelets/megakaryocytes (MKs), the key components in the blood system, in the tumor microenvironment and antitumor immunity are unclear. In patients with colorectal cancer, the number of platelets was significantly increased in patients with metastasis, and Erbin expression was highly expressed in platelets from patients with metastases. Moreover, Erbin knockout in platelets/MKs suppressed lung metastasis in mice and promoted aggregations of platelets. Mechanistically, Erbin-deficient platelets have increasing mitochondrial oxidative phosphorylation and secrete lipid metabolites like acyl-carnitine (Acar) by abolishing interaction with prothrombotic protein ESAM. Notably, Acar enhanced the activity of mitochondrial electron transport chain complex and mitochondrial oxidative phosphorylation in B cells by acetylation of H3K27 epigenetically. Targeting Erbin in platelets/MKs by a nanovesicle system dramatically attenuated lung metastasis in mice in vivo. Our study identifies an Erbin-mitochondria axis in platelets/MKs, which suppresses B cell-mediated antitumor immunity, suggesting a new way for the treatment of metastasis.

Influence of substrate temperature on the properties of ZnTe:Cu films prepared by a magnetron co-sputtering method.

Copper-doped Zinc Tellurium (ZnTe:Cu) films were deposited on borosilicate glass using magnetron co-sputtering technique. The influence of the substrate temperature on the structural, morphological, optical and electrical properties of ZnTe:Cu films was investigated by X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), UV-Vis spectrophotometer and Hall effect measurement system. The results indicate that substrate temperature significantly affects the properties of the ZnTe:Cu films. When the substrate temperature increases from room temperature to 600 °C, the (111)-preferred orientation of ZnTe:Cu films is gradually replaced by the (220)-preferred orientation. At high substrate temperatures (≥500 °C), the CuxTe phase appears in the ZnTe:Cu films, resulting in higher carrier concentration (>1019 cm-3) and lower resistivity (<10-2 Ω cm) of the prepared films.

The potential of marine-derived piperazine alkaloids: Sources, structures and bioactivities.

Marine-derived piperazine alkaloids (MDPAs) constitute a significant group of natural compounds known for their diverse structures and biological activities. Over the past five decades, substantial efforts have been devoted to isolating these alkaloids from marine sources and characterizing their chemical and bioactive profiles. To date, a total of 922 marine-derived piperazine alkaloids have been reported from various marine organisms. These compounds demonstrate a wide range of pharmacological properties, including cytotoxicity, antibacterial, antifungal, antiviral, and various other activities. Notably, among these activities, cytotoxicity emerges as the most prominent characteristic of marine-derived piperazine alkaloids. This review also summarizes the structure-activity relationship (SAR) studies associated with the cytotoxicity of these compounds. In summary, our objective is to provide an overview of the research progress concerning marine-derived piperazine alkaloids, with the aim of fostering their continued development and utilization.

An ultrasensitive cellulose-based fluorescent sensor for Al3+ detection and its applications in plant tissue and food samples.

Fluorescent sensors available for metal ions detection have been extensively developed in recent years. However, developing an ultrasensitive fluorescent sensor for highly selectively detecting Al3+ based on cellulose remains a challenge. In this study, an ethylcellulose-based flavonol fluorescent sensor named EC-BHA was synthesized by the esterification of ethylcellulose (EC) with a new flavonol derivative 4-(2-(2,3-bis(ethoxymeothy)phenyl)-3-hydroxy-4-oxo-4-H-chromen-7-yl) benzoic acid (BHA). The fluorescence intensity of EC-BHA exhibited a 180-fold increase at 490 nm after binding with Al3+ and provided an ultralow detection limit of 13.0 nM. The sensor showed some exceptional sensing properties including a broad pH range (4-10), large Stokes shifts (190 nm), and a short response time (3 min). This sensor was successfully applied for determining trace Al3+ in food samples as well as in plant tissue. Moreover, the electrostatic spun film EBP was fabricated by blending EC-BHA with PS (polystyrene) via electrostatic spinning technique and utilized for selective detection of Al3+ as soon as possible.

The mixed effect of Endocrine-Disrupting chemicals on biological age Acceleration: Unveiling the mechanism and potential intervention target.

INTRODUCTION: Although previous studies investigated the potential adverse effects of endocrine-disrupting chemicals (EDCs) on biological age acceleration and aging-related diseases, the mixed effect of multiple types of EDCs on biological age acceleration, including its potential underlying mechanism, remains unclear. METHODS: Data from the National Health and Nutrition Examination Survey (NHANES) were used to analyze biological age measures, including Klemera-Doubal method biological age (KDM-BA), phenotypic age, and homeostatic dysregulation (HD). Weight quantile sum (WQS) regression was performed to screen biological age-related EDCs (BA-EDCs) and assess the mixed effect of BA-EDCs on biological age acceleration and aging-related disease. Targets of BA-EDCs were obtained from three databases, while heart aging-related genes were obtained from the Aging Anno database. Protein-protein interaction (PPI) network and MCODE algorithm were applied to identify potential interactions between BA-EDC targets and heart aging-related genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to identify related pathways. RESULTS: This cross-sectional study included 1,439 participants. A decile increase in BA-EDCs co-exposure was associated with 0.31 years and 0.17 years of KDM-BA and phenotypic age acceleration, respectively. The mixed effect of BA-EDCs was associated with an increased prevalence of atherosclerotic cardiovascular disease (ASCVD). Vitamins C and E demonstrated a significant interaction effect on the association between BA-EDCs and KDM-BA acceleration. PPI network and functional enrichment analysis indicated that the AGE-RAGE signaling pathway in diabetic complications was significantly enriched. CONCLUSION: Our results showed that the co-exposure effect of BA-EDCs was associated with biological age acceleration and ASCVD, with the AGE-RAGE signaling pathway being the underlying mechanism. Vitamins C and E may also be an actionable target for preventing EDC-induced biological aging.