Identification of bladder cancer subtypes and predictive model for prognosis, immune features, and immunotherapy based on neutrophil extracellular trap-related genes.

Bladder cancer is the most common malignant tumor of urinary system, and its morbidity and mortality are increasing rapidly. Although great advances have been made in medical technology in recent years, there is still a lack of effective prognostic and therapeutic methods for bladder cancer. NETs are reticulated DNA structures decorated with various protein substances released extracellularly by neutrophils stimulated by strong signals. Recently, it has been found that NETs are closely related to the growth, metastasis and drug resistance of many types of cancers. However, up to now, the research on the relationship between NETs and bladder cancer is still not enough. In this study, we aimed to conduct a comprehensive analysis of NRGs in bladder cancer tissues to evaluate the relationship between NRGs and prognosis prediction and sensitivity to therapy in patients with bladder cancer. We scored NRGs in each tissue by using ssGSEA, and selected gene sets that were significantly associated with NRGs scores by using the WCGNA algorithm. Based on the expression profiles of NRGs-related genes, NMF clustering analysis was performed to identify different BLCA molecular subtypes. For the differentially expressed genes between subtypes, we used univariate COX regression, LASSO regression and multivariate COX regression to further construct a hierarchical model of BLCA patients containing 10 genes. This model and the nomogram based on this model can accurately predict the prognosis of BLCA patients in multiple datasets. Besides, BLCA patients classified based on this model differ greatly in their sensitivity to immunotherapy and targeted therapies, which providing a reference for individualized treatment of patients with bladder cancer.

Controllable Synthesis of Monolayer Poly(acrylic acid) on the Channel Surface of Mesoporous Alumina for Pb(II) Adsorption.

Polymer/inorganic nanocomposites exhibit special properties due to highly intimate interactions between organic and inorganic phases and thus have been deployed for various applications. Among them, nanocomposites with monolayer polymer coverage on the inorganic surface demonstrate the highest efficiency for applications. However, the controllable synthesis of the polymer monolayer in mesopores of inorganic substrates remains a challenge. In this study, poly(acrylic acid)/γ-alumina nanocomposites (PAA/alumina) were synthesized via the in situ polymerization of acrylic acid impregnated in mesopores of alumina. By applying the preneutralization of monomers, the polymerization was found to be highly controllable in generating monolayer PAA coverage. The formation of monolayers was verified by thermogravimetry, semiquantitative Fourier transform infrared spectroscopy, N2 adsorption-desorption, and Pb(II) adsorption. Alternatively, the organic loadings of PAA/alumina composite samples could be controlled in the range of 0.2 to 1.0 equiv of monolayer, together with the linearly correlated metal ion adsorption capacity. As calculated by the complexation model, one Pb(II) is combined with two carboxylate groups of PAA. The formation of the monolayer polymer inside mesoporous oxide channels represents a method for the development of highly promising functional nanocomposites.