Search

Abstract Acute lung injury (ALI) is the result of damage to the capillary endothelia and the alveolar epithelial cell caused by various direct and indirect factors, leading to significant pulmonary interstitial and alveolar edema and acute hypoxic respiratory insufficiency. A subset of ALI cases progresses to irreversible pulmonary fibrosis, a condition with fatal implications. Zafirlukast is a leukotriene receptor antagonist licensed for asthma prevention and long-term treatment. This study demonstrated a significant improvement in lung tissue pathology and a reduction in inflammatory cell infiltration in models of lipopolysaccharide (LPS)-induced ALI and bleomycin (BLM)-induced lung inflammation following zafirlukast administration, both in vivo and in vitro. Moreover, zafirlukast was found to suppress the inflammatory response of alveolar epithelial cells in vitro and lung inflammation in vivo by reducing the activation of the TLR4/NF-κB/NLRP3 inflammasome pathway. In conclusion, zafirlukast relieved lung injury and the infiltration of inflammatory cells in the lung by regulating the TLR4/NF-κB/NLRP3 pathway.

Abstract Defensive capability is one of the essential attributes of traditional military settlements. In the Ming dynasty, coastal Wei fort was the one of the most functionally complex and wide-ranging fortifications in the military defense system of China. Because many factors affect their defensive capacities, including three dimensions: individual construction, synergistic links, and regional jurisdiction, it is not easy to compare different settlements’ defensive capacities or to judge the degrees of different factors’ influences. Through principal component analysis, this study determines the weights of each minor factor. It constructs a model for evaluating traditional Chinese military settlements’ defensive capabilities, to quantify the defensive capability. The results show that the synergistic relationship between the settlements, especially settlement accessibility, has the most significant impact on defensive capability, much higher than a single castle's defensive construction. The defensive capability index of the Wei forts in Guangdong is the highest, consistent with the highest rate of victory in the wars fought on the coast during the Ming dynasty. The defensive capacity is directly proportional to the rate of victory, which validates this evaluation model’s soundness. This study not only comprehensively evaluates the coastal Wei forts’ defensive capacity in the Ming Dynasty, but also provides new methods for the quantitative or comparative analysis of military settlements at other temporal and spatial scales.

Abstract Cuproptosis and disulfidptosis, recently discovered mechanisms of cell death, have demonstrated that differential expression of key genes and long non-coding RNAs (lncRNAs) profoundly influences tumor development and affects their drug sensitivity. Clear cell renal cell carcinoma (ccRCC), the most common subtype of kidney cancer, presently lacks research utilizing cuproptosis and disulfidptosis-related lncRNAs (CDRLRs) as prognostic markers. In this study, we analyzed RNA-seq data, clinical information, and mutation data from The Cancer Genome Atlas (TCGA) on ccRCC and cross-referenced it with known cuproptosis and disulfidptosis-related genes (CDRGs). Using the LASSO machine learning algorithm, we identified four CDRLRs—ACVR2B-AS1, AC095055.1, AL161782.1, and MANEA-DT—that are strongly associated with prognosis and used them to construct a prognostic risk model. To verify the model's reliability and validate these four CDRLRs as significant prognostic factors, we performed dataset grouping validation, followed by RT-qPCR and external database validation for differential expression and prognosis of CDRLRs in ccRCC. Gene function and pathway analysis were conducted using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) for high- and low-risk groups. Additionally, we have analyzed the tumor mutation burden (TMB) and the immune microenvironment (TME), employing the oncoPredict and Immunophenoscore (IPS) algorithms to assess the sensitivity of diverse risk categories to targeted therapeutics and immunosuppressants. Our predominant objective is to refine prognostic predictions for patients with ccRCC and inform treatment decisions by conducting an exhaustive study on cuproptosis and disulfidptosis.

BackgroundNatural infection or vaccination have provided robust immune defense against SARS-CoV-2 invasion, nevertheless, Omicron variants still successfully cause breakthrough infection, and the underlying mechanisms are poorly understood.MethodsSequential blood samples were continuously collected at different time points from 252 volunteers who were received the CanSino Ad5-nCoV (n= 183) vaccine or the Sinovac CoronaVac inactivated vaccine (n= 69). The anti-SARS-CoV-2 prototype and Omicron BA.5.2 as well as XBB.1.16 variant neutralizing antibodies (Nab) in sera were detected by ELISA. Sera were also used to measure pseudo and live virus neutralization assay. The associations between the anti-prototype Nab levels and different HLA-ABC alleles were analyzed using artificial intelligence (AI)-deep learning techniques. The frequency of B cells in PBMCs was investigated by flow cytometry assay (FACs).ResultsIndividuals carrying the HLA-B*15 allele manifested the highest concentrations of anti-SARS-CoV-2 prototype Nab after vax administration. Unfortunately, these volunteers are more susceptible to Omicron BA.5.2 breakthrough infection due to their sera have poorer anti-BA.5.2 Nab and lower levels of viral neutralization efficacy. FACs confirmed that a significant decrease in CD19+CD27+RBD+ memory B cells in these HLA-B*15 population compared to other cohorts. Importantly, generating lower concentrations of cross-reactive anti-XBB.1.16 Nab post-BA.5.2 infection caused HLA-B*15 individuals to be further infected by XBB.1.16 variant.ConclusionsIndividuals carrying the HLA-B*15 allele respond better to COVID-19 vax including the CanSino Ad5-nCoV and the Sinovac CoronaVac inactivated vaccines, but are more susceptible to Omicron variant infection, thus, a novel vaccine against this population is necessary for COVID-19 pandemic control in the future.

CO2 reduction by CH4 (CRM) to produce fuel is of great significance for solar energy storage and eliminating greenhouse gas. Herein, the catalyst of ultrafine Ni nanoparticles supported on CeZrNiO2 solid solution (Ni@CZNO) was synthesized by the sol-gel method. High yield of H2 and CO (58.0 and 69.8 ​mmol ​min−1 ​g−1) and excellent durability (50 ​h) were achieved by photothermal catalytic CRM merely under focused light irradiation. Structural characterization and DFT calculations reveal that CZNO has rich oxygen vacancies that can adsorb and activate CO2 to produce reactive oxygen species. Oxygen species are transferred to ultrafine Ni nanoparticles through the rich Ni-CZNO interface to accelerate carbon oxidation, thereby maintaining the excellent catalytic stability of the catalyst. Moreover, the experimental results reveal that light irradiation can not only enhance the photothermal catalytic CRM activity through photothermal conversion and molecular activation, but also improve the stability by increasing the concentration of oxygen vacancies and inhibiting CO disproportionation.

The deep learning method has been widely used in the engineering field. The availability of the training dataset is one of the most important limitations of the deep learning method. Accurate prediction of pavement performance plays a vital role in road preventive maintenance (PM) and decision-making. Pavement performance prediction based on deep learning has been widely used around the world for its accuracy, robustness, and automation. However, most of the countries in the world have not built their pavement performance historical database, which prevents preventive maintenance using the deep learning method. This study presents an innovative particle swarm optimization (PSO) algorithm-enhanced two-stage TrAdaBoost.R2 transfer learning algorithm, which could significantly increase the pavement performance prediction database. The Long-Term Pavement Performance (LTPP) database is used as the source domain data, and one of the highways in China is chosen as the target domain to predict pavement performance. The results show that the proposed PSO-Two-stage TrAdaBoost.R2 model has the highest accuracy compared with AdaBoost.R2 model and traditional regression decision tree model. The validation case study shows significant consistency between the predicted International Roughness Index (IRI) and the whole-year measurement data with an R2 of 0.7. This study demonstrates the great potential of the innovative instance-based transfer learning method in pavement performance prediction of a region’s lack of data. This study also contributes to other engineering fields that could greatly increase the universality of deep learning.

Idiopathic pulmonary fibrosis (IPF) is an incurable chronic progressive disease with a low survival rate and ineffective therapeutic options. We examined the effects of imrecoxib, a nonsteroidal anti-inflammatory drug, on experimental pulmonary fibrosis. The mouse IPF model was established by intratracheal instillation of bleomycin. From Day 0 to Day 13, the mice were orally administered imrecoxib (100 mg/kg) and pirfenidone (200 mg/kg) daily, and from Day 7 to Day 13, the mice were orally administered pirfenidone and imrecoxib daily. The tissues were dissected on the 14th day. Mouse body weight was measured, and histopathological examination and hydroxyproline content analysis confirmed that the administration of imrecoxib exerted a similar effect to pirfenidone. Compared with bleomycin-induced mice, imrecoxib-treated mice showed significantly reduced inflammatory factor expression (IL-1 and TNF-α) and inflammatory cell numbers (macrophages, lymphocytes, and neutrophils) in BALF (bronchoalveolar lavage fluid). Our experiment tested the ability of imrecoxib to inhibit the signal pathway involved in gene expression induced by TGF-β1 in the NIH-3T3 cell line in vitro. Western blotting showed that imrecoxib (20 μM and 40 μM) inhibited the expression of fibronectin, type I collagen and CTGF. In addition, imrecoxib reduced the levels of p-ERK1/2. The changes in the expression of related proteins in mouse lung tissue were similar to those in cells. In summary, our findings suggested that the administration of imrecoxib prevented and treated murine IPF by inhibiting inflammation and the TGF-β1-ERK1/2 signaling pathway.

(1) Background: Heart failure (HF) is the final stage of multiple cardiac diseases, which have now become a severe public health problem worldwide. β-Adrenergic receptor (β-AR) overactivation is a major pathological factor associated with multiple cardiac diseases and mediates cardiac fibrosis and inflammation. Previous research has demonstrated that Bruton’s tyrosine kinase (BTK) mediated cardiac fibrosis by TGF-β related signal pathways, indicating that BTK was a potential drug target for cardiac fibrosis. Zanubrutinib, a second-generation BTK inhibitor, has shown anti-fibrosis effects in previous research. However, it is unclear whether Zanubrutinib can alleviate cardiac fibrosis induced by β-AR overactivation; (2) Methods: In vivo: Male C57BL/6J mice were treated with or without the β-AR agonist isoproterenol (ISO) to establish a cardiac fibrosis animal model; (3) Results: In vivo: Results showed that the BTK inhibitor Zanubrutinib (ZB) had a great effect on cardiac fibrosis and inflammation induced by β-AR. In vitro: Results showed that ZB alleviated β-AR-induced cardiac fibroblast activation and macrophage pro-inflammatory cytokine production. Further mechanism studies demonstrated that ZB inhibited β-AR-induced cardiac fibrosis and inflammation by the BTK, STAT3, NF-κB, and PI3K/Akt signal pathways both in vivo and in vitro; (4) Conclusions: our research provides evidence that ZB ameliorates β-AR-induced cardiac fibrosis and inflammation.

In this work, poly(ether ether ketone) (PEEK) was synthesized by direct polycondensation reaction. Subsequently, PEEK was functionalized by 1-vinylimidazole to prepare the polymer matrix (Im-PEEK). Cationic UiO-66-NH2 metal-organic frameworks (C-MOF) were synthesized as fillers. The structure of the C-MOF and the morphology of the membranes were verified by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) and field emission scanning electron microscopy (FE-SEM). The prepared hybrid membranes exhibited excellent alkali stability, among which Im-PEEK/C-MOF-1% could retain 89.2% of the conductivity compared to the original membrane after immersing in 1 ​mol ​L−1 NaOH solution for 320 ​h at 60 ​°C. In addition, the ionic conductivity of Im-PEEK/C-MOF-1% was 73 ​mS ​cm−1 at 80 ​°C, which was higher than that of pure Im-PEEK under the same condition (44.3 ​mS ​cm−1 at 80 ​°C). The results showed that the hybrid membranes have great potential for application in the field of anion exchange membranes.

BackgroundImmune checkpoint inhibitors (ICIs) have become a high-profile regimen for malignancy recently. However, only a small subpopulation obtains long-term clinical benefit. How to select optimal patients by reasonable biomarkers remains a hot topic.MethodsPaired tissue samples and blood samples from 51 patients with advanced malignancies were collected for correlation analysis. Dynamic changes in blood PD-L1 (bPD-L1) expression, including PD-L1 mRNA, exosomal PD-L1 (exoPD-L1) protein and soluble PD-L1 (sPD-L1), were detected after 2 months of ICIs treatment in advanced non-small-cell lung cancer (NSCLC) patients. The best cutoff values for progression-free survival (PFS) and overall survival (OS) of all three biomarkers were calculated with R software.ResultsIn 51 cases of various malignancies, those with positive tissue PD-L1 (tPD-L1) had significantly higher PD-L1 mRNA than those with negative tPD-L1. In 40 advanced NSCLC patients, those with a fold change of PD-L1 mRNA ≥ 2.04 had better PFS, OS and best objective response (bOR) rate. In addition, a fold change of exoPD-L1 ≥ 1.86 was also found to be associated with better efficacy and OS in a cohort of 21 advanced NSCLC cases. The dynamic change of sPD-L1 was not associated with efficacy and OS. Furthermore, the combination of PD-L1 mRNA and exoPD-L1 could screen better patients for potential benefit from ICIs treatment.ConclusionThere was a positive correlation between bPD-L1 and tPD-L1 expression. Increased expression of PD-L1 mRNA, exoPD-L1, or both in early stage of ICIs treatment could serve as positive biomarkers of efficacy and OS in advanced NSCLC patients.

CO2 reduction by CH4 (CRM) to produce fuel is of great significance for solar energy storage and eliminating greenhouse gas. Herein, the catalyst of ultrafine Ni nanoparticles supported on CeZrNiO2 solid solution (Ni@CZNO) was synthesized by the sol-gel method. High yield of H2 and CO (58.0 and 69.8 mmol min-1 g-1) and excellent durability (50 h) were achieved by photothermal catalytic CRM merely under focused light irradiation. Structural characterization and DFT calculations reveal that CZNO has rich oxygen vacancies that can adsorb and activate CO2 to produce reactive oxygen species. Oxygen species are transferred to ultrafine Ni nanoparticles through the rich Ni-CZNO interface to accelerate carbon oxidation, thereby maintaining the excellent catalytic stability of the catalyst. Moreover, the experimental results reveal that light irradiation can not only enhance the photothermal catalytic CRM activity through photothermal conversion and molecular activation, but also improve the stability by increasing the concentration of oxygen vacancies and inhibiting CO disproportionation. [ABSTRACT FROM AUTHOR]