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Liquid rubber (LR) has been proven to be a valuable asphalt modifier capable of addressing the existing deficiencies associated with crumb rubber–modified asphalt (CRMA), including poor workability and storage stability. Therefore, an accessible preparation method based on olefin metathesis was explored to produce optimal LR from crumb rubber (CR) in the laboratory. This research established the optimal laboratory preparation conditions for LR and investigated the performance of liquid rubber–modified asphalt (LRMA) mixture when used in pavement. A total of 32 LR samples were generated by olefin metathesis and physical swelling under various catalytic and swelling conditions. The physical properties, viscosity, and storage ability of LRMA were evaluated to select the optimal preparation parameters for LR. A comprehensive analysis was performed to compare the physicochemical characteristics of LR and the original CR through microscopic examinations with scanning electron microscopy (SEM), Fourier-transform infrared spectrometry (FTIR), and gel permeation chromatography (GPC). An in-depth evaluation assessed the stability at high temperatures, the properties at low temperatures, and the moisture stability of LRMA and CRMA mixtures. Experimental results showed that the optimal laboratory preparation conditions for LR were a catalyst dosage between 3‰ and 5‰, a catalytic duration of 48 h, a swelling temperature of 160°C, and a swelling time of 8 h. Moreover, LR possessed a smooth surface without rubber particles. The molecular weight and distribution of LR were considerably reduced compared with those of CR after olefin metathesis and physical swelling. The introduction of LR significantly enhanced the cracking resistance of the base asphalt mixture. However, the enhancement effect of LR on the base asphalt mixture to resist high-temperature rutting and moisture damage was inferior to that of CR. [ABSTRACT FROM AUTHOR]

Non-small-cell lung carcinoma (NSCLC) often carries a dire prognosis. The advent of neoadjuvant chemoimmunotherapy (NCI) has become a promising approach in NSCLC treatment, making the identification of reliable biomarkers for major pathological response (MPR) crucial. This study aimed to devise a deep learning (DL) model to estimate the MPR to NCI in lung squamous cell carcinoma (LUSC) patients and uncover its biological mechanism. We enrolled a cohort of 309 LUSC patients from various medical institutions. A ResNet50 model, trained on contrast-enhanced computed tomography images, was developed, and validated to predict MPR. We examined somatic mutations, genomic data, tumor-infiltrating immune cells, and intra-tumor microorganisms. Post-treatment, 149 (48.22%) patients exhibited MPR. The DL model demonstrated excellent predictive accuracy, evidenced by an area under the receiver operating characteristic curve (AUC) of 0.95 (95% CI: 0.98-1.00) and 0.90 (95% CI: 0.81-0.98) in the first and second validation sets, respectively. Multivariate logistic regression analysis identified the DL model score (low vs. high) as an independent predictor of MPR. The prediction of MPR (P-MPR) correlated with mutations in four genes, as well as gene ontology and pathways tied to immune response and antigen processing and presentation. Analysis also highlighted diversity in immune cells within the tumor microenvironment and in peripheral blood. Moreover, the presence of four distinct bacteria varied among intra-tumor microorganisms. Our DL model proved highly effective in predicting MPR in LUSC patients undergoing NCI, significantly advancing our understanding of the biological mechanisms involved.

Vehicle exhaust seriously pollutes urban air and harms human health. Photocatalytic technology can effectively degrade automobile exhaust. This work prepared g-C 3 N 4 /CeO 2 photocatalytic material by constructing heterojunctions. Four kinds of g-C 3 N 4 /CeO 2 composite photocatalytic materials with different mass ratios were prepared. An indoor exhaust gas purification test was carried out under natural light and ultraviolet light irradiations. The optimum mass ratio of g-C 3 N 4 material and CeO 2 material was determined by evaluating the exhaust gas degradation effective. Moreover, the structure and morphology of the g-C 3 N 4 /CeO 2 composite were investigated with microscopic characterization experiments (including XRD, TG-DSC, FT-IR, UV-Vis, SEM and XPS). The results obtained were that the optimum mass ratio of g-C 3 N 4 material to CeO 2 material was 0.75. The degradation efficiencies under ultraviolet irradiation in 60 min for HC, CO, CO 2 , NO X were 7.59%, 12.10%, 8.25% and 36.82%, respectively. Under visible light conditions, the degradation efficiency in 60 min for HC, CO, CO 2 and NO X were 15.88%, 16.22%, 10.45% and 40.58%, respectively. This work is useful for purifying automobile exhaust in the future.