Membranes Based on “Keplerate”-Type Polyoxometalates: Slow, Passive Cation Transportation and Creation of Water Microenvironment

We report a novel type of inorganic membranelike structure formed by the self-assembly of hydrophilic polyoxometalate macroanions. Such nanoscaled, water-soluble macroions tend to form stable, uniform, single-layer “blackberry” structures (20−1000 nm in size) in dilute solutions via noncovalent bond interactions. Two interesting features of “Keplerate” {Mo72Fe30} blackberries are found from fluorescence studies:  (1) They create a microscaled, relatively isolated water environment (containing over 3 million water molecules) which possesses different properties from the bulk water. (2) The blackberry membrane is permeable to small cations, but not to anions. The passive transport of cations across the blackberry membrane is relatively slow but does not need any carrier or additional energy

Self-Assembly of Organic−Inorganic Hybrid Amphiphilic Surfactants with Large Polyoxometalates as Polar Head Groups

Self-Assembly of Organic−Inorganic Hybrid Amphiphilic Surfactants with Large Polyoxometalates as Polar Head Group

Synthesis of Stishovite Nanocrystals from Periodic Mesoporous Silica

Synthesis of Stishovite Nanocrystals from Periodic Mesoporous Silic

Lag Periods During the Self-Assembly of {Mo₇₂Fe₃₀} Macroions: Connection to the Virus Capsid Formation Process

The kinetic properties of the self-assembly of hydrophilic Keplerate-type polyoxometalate (POM) {Mo72Fe30} macroanions into single-layer, vesicle-like blackberry structures in solutions were monitored by the static and dynamic laser light scattering techniques. In the presence of additional electrolytes, an obvious lag period at the initial stage of self-assembly was observed, followed by a fast increase of the scattered intensity. The whole kinetic curve is sigmoidal with a lag phase. A two-step nucleation−growth mechanism is proposed to explain this lag phase: the {Mo72Fe30} macroanions slowly associate into oligomers (mostly dimers), which are the thermodynamically unfavorable intermediates, at the initial stage; once the oligomers reach a critical concentration, the blackberry formation process is accelerated. Analytical ultracentrifugation (AUC) was used to confirm the oligomeric state in {Mo72Fe30} solution during the lag period. The length of the lag period is dependent on temperature, ionic strength, and the valent states of the additional salts, as well as the solvent content. The kinetics (including the lag period) of the blackberry formation of the {Mo72Fe30} macroanions show similarities to the self-assembly of virus capsid proteins (which are also soluble macroions) into spherical capsid shells, suggesting possible connections between the self-assembly behaviors of inorganic species and biological macromolecules

MOESM1 of Association of TNFAIP8 gene polymorphisms with endometrial cancer in northern Chinese women

Additional file 1: Table S1. Stratified analysis between TNFAIP8 SNPs and endometrial cancer risk by age

Table3_Immunogenic cell death-related gene landscape predicts the overall survival and immune infiltration status of ovarian cancer.DOCX

Background: Ovarian cancer (OC) is the most troubling malignant tumor of the female reproductive system. It has a low early diagnosis rate and a high tumor recurrence rate after treatment. Immunogenic cell death (ICD) is a unique form of regulated cell death that can activate the adaptive immune system through the release of DAMPs and cytokines in immunocompromised hosts and establish long-term immunologic memory. Therefore, this study aims to explore the prognostic value and underlying mechanisms of ICD-related genes in OC on the basis of characteristics.Methods: The gene expression profiles and related clinical information of OC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. ICD-related genes were collected from the Genecards database. ICD-related prognostic genes were obtained by intersecting ICD-related genes with the OC prognostic-related genes that were analyzed in the TCGA database. Functional enrichment, genetic mutation, and immune infiltration correlation analyses were further performed to identify underlying mechanisms. Subsequently, we developed a TCGA cohort-based prognostic risk model that included a nine-gene signature through univariate and multivariate Cox regression and LASSO regression analyses. Meanwhile, external validation was performed on two sets of GEO cohorts and the TCGA training cohort for three other common tumors in women. In addition, a nomogram was established by integrating clinicopathological features and ICD-related gene signature to predict survival probability. Finally, functional enrichment and immune infiltration analyses were performed on the two risk subgroups.Results: By utilizing nine genes (ERBB2, RB1, CCR7, CD38, IFNB1, ANXA2, CXCL9, SLC9A1, and SLAMF7), we constructed an ICD-related prognostic signature. Subsequently, patients were subdivided into high- and low-risk subgroups in accordance with the median value of the risk score. In multivariate Cox regression analyses, risk score was an independent prognostic factor (hazard ratio = 2.783; p Conclusion: We constructed a novel ICD-related gene model for forecasting the prognosis and immune infiltration status of patients with OC. In the future, new ICD-related genes may provide novel potential targets for the therapeutic intervention of OC.</p

Table1_Immunogenic cell death-related gene landscape predicts the overall survival and immune infiltration status of ovarian cancer.XLSX

Background: Ovarian cancer (OC) is the most troubling malignant tumor of the female reproductive system. It has a low early diagnosis rate and a high tumor recurrence rate after treatment. Immunogenic cell death (ICD) is a unique form of regulated cell death that can activate the adaptive immune system through the release of DAMPs and cytokines in immunocompromised hosts and establish long-term immunologic memory. Therefore, this study aims to explore the prognostic value and underlying mechanisms of ICD-related genes in OC on the basis of characteristics.Methods: The gene expression profiles and related clinical information of OC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. ICD-related genes were collected from the Genecards database. ICD-related prognostic genes were obtained by intersecting ICD-related genes with the OC prognostic-related genes that were analyzed in the TCGA database. Functional enrichment, genetic mutation, and immune infiltration correlation analyses were further performed to identify underlying mechanisms. Subsequently, we developed a TCGA cohort-based prognostic risk model that included a nine-gene signature through univariate and multivariate Cox regression and LASSO regression analyses. Meanwhile, external validation was performed on two sets of GEO cohorts and the TCGA training cohort for three other common tumors in women. In addition, a nomogram was established by integrating clinicopathological features and ICD-related gene signature to predict survival probability. Finally, functional enrichment and immune infiltration analyses were performed on the two risk subgroups.Results: By utilizing nine genes (ERBB2, RB1, CCR7, CD38, IFNB1, ANXA2, CXCL9, SLC9A1, and SLAMF7), we constructed an ICD-related prognostic signature. Subsequently, patients were subdivided into high- and low-risk subgroups in accordance with the median value of the risk score. In multivariate Cox regression analyses, risk score was an independent prognostic factor (hazard ratio = 2.783; p Conclusion: We constructed a novel ICD-related gene model for forecasting the prognosis and immune infiltration status of patients with OC. In the future, new ICD-related genes may provide novel potential targets for the therapeutic intervention of OC.</p

MOESM3 of Association of TNFAIP8 gene polymorphisms with endometrial cancer in northern Chinese women

Additional file 3: Table S3. Stratified analysis between TNFAIP8 SNPs and endometrial cancer risk by BMI

Table2_Immunogenic cell death-related gene landscape predicts the overall survival and immune infiltration status of ovarian cancer.DOCX

Background: Ovarian cancer (OC) is the most troubling malignant tumor of the female reproductive system. It has a low early diagnosis rate and a high tumor recurrence rate after treatment. Immunogenic cell death (ICD) is a unique form of regulated cell death that can activate the adaptive immune system through the release of DAMPs and cytokines in immunocompromised hosts and establish long-term immunologic memory. Therefore, this study aims to explore the prognostic value and underlying mechanisms of ICD-related genes in OC on the basis of characteristics.Methods: The gene expression profiles and related clinical information of OC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. ICD-related genes were collected from the Genecards database. ICD-related prognostic genes were obtained by intersecting ICD-related genes with the OC prognostic-related genes that were analyzed in the TCGA database. Functional enrichment, genetic mutation, and immune infiltration correlation analyses were further performed to identify underlying mechanisms. Subsequently, we developed a TCGA cohort-based prognostic risk model that included a nine-gene signature through univariate and multivariate Cox regression and LASSO regression analyses. Meanwhile, external validation was performed on two sets of GEO cohorts and the TCGA training cohort for three other common tumors in women. In addition, a nomogram was established by integrating clinicopathological features and ICD-related gene signature to predict survival probability. Finally, functional enrichment and immune infiltration analyses were performed on the two risk subgroups.Results: By utilizing nine genes (ERBB2, RB1, CCR7, CD38, IFNB1, ANXA2, CXCL9, SLC9A1, and SLAMF7), we constructed an ICD-related prognostic signature. Subsequently, patients were subdivided into high- and low-risk subgroups in accordance with the median value of the risk score. In multivariate Cox regression analyses, risk score was an independent prognostic factor (hazard ratio = 2.783; p Conclusion: We constructed a novel ICD-related gene model for forecasting the prognosis and immune infiltration status of patients with OC. In the future, new ICD-related genes may provide novel potential targets for the therapeutic intervention of OC.</p