Fabrication of Copper Hydroxyphosphate with Complex Architectures

Copper hydroxyphosphate [Cu2(OH)PO4] with complex architectures has been synthesized through a simple and mild hydrothermal route in the absence of any external inorganic additives or organic structure-directing templates. Powder X-ray diffraction, scanning electron microscopy, and Fourier transform infrared spectrometry are used to characterize various properties of the obtained samples. Single-crystals, twinned-crystals, and various novel architectures of copper hydroxyphosphate can be constructed through a careful control of synthetic parameters, such as the molar ratio of initial reagents, reagent concentration, reaction time, and temperature. On the basis of structure and chemical bond analysis, copper hydroxyphosphate crystals tend to grow along the c-axis and have a rotation twinned-crystal growth habit, which is essential for the formation of various complex architectures. The current approach provides a facile strategy to synthesize copper hydroxyphosphate crystals with unique morphologies and complex architectures, which may be applicable to the synthesis of other inorganic materials

Fabrication of Upended Taper-Shaped Cuprous Thiocyanate Arrays on a Copper Surface at Room Temperature

A new strategy has been well designed to form upended taper-shaped cuprous thiocyanate (hereafter abbreviated as CuCNS) arrays on a copper substrate with use of a simple solution-phase method at room temperature. This method consists of a liquid−solid reaction between a solution of thiocyanate ammonium and the copper substrate itself in the assistance of formamide. Novel CuCNS arrays are approximately perpendicular to copper substrate surfaces. Every single crystal shows an upended taper-like morphology (i.e., the tip end points into the surface of copper substrate and the other big end of the taper exposes out, like a dart thrusting into the copper substrate). On the basis of structure and chemical bond analysis, CuCNS crystals tend to grow along the c-axis, which is essential for the formation of CuCNS arrays on a copper substrate. This approach also provides a facile strategy to produce different patterns on different copper substrates, which may be applicable to the synthesis of other inorganic materials with various potential applications

Fabrication of Malachite with a Hierarchical Sphere-like Architecture

Malachite (Cu2(OH)2CO3) with a hierarchical sphere-like architecture has been successfully synthesized via a simple and mild hydrothermal route in the absence of any external inorganic additives or organic structure-directing templates. Powder X-ray diffraction, scanning electron microscopy, and Fourier transmission infrared spectrometry are used to characterize various properties of the obtained malachite samples. The hierarchical malachite particles are uniform spheres with a diameter of 10−20 μm, which are comprised of numerous two-dimensional microplatelets paralleling the sphere surface. The initial concentration of reagents, the hydrothermal reaction time, and temperature are important factors which dominantly affect the evolution of crystal morphologies. The growth of the hierarchical architecture is believed to be a layer-by-layer growth process. Further, copper oxide with the similar morphology can be easily obtained from the as-prepared malachite

Room Temperature Synthesis of Curved Ammonium Copper Molybdate Nanoflake and Its Hierarchical Architecture

A new strategy has been successfully designed to synthesize curved ammonium copper molybdate [(NH4)2Cu(MoO4)2] nanoflakes on a copper surface by employing a novel solution-phase approach at room temperature. This method consists of a liquid−solid reaction between Na2MoO4 solution and the copper substrate itself in the assistance of formamide. The lamellar ammonium copper molybdate are approximately perpendicular to the copper substrate surface and are intermeshed with each other to form nanogroove structures. Formamide molecules cannot only promote the oxidation of copper substrate and the formation of copper complex, but also act as a NH4+ source in the final products. Furthermore, the selective adsorption of formamide molecules on different crystallographic planes of ammonium copper molybdate plays the major role in determining the curved morphology. In addition, using glucose as additives to control the nucleation and growth process (through a stepwise nucleation mechanism) can lead to a hierarchical sphere-like architecture

Image_5_Differential Expression of the TLR4 Gene in Pan-Cancer and Its Related Mechanism.jpg

Previous studies have revealed the relationship between toll-like receptor 4 (TLR4) polymorphisms and cancer susceptibility. However, the relationship between TLR4 and prognosis and immune cell infiltration in pan-cancer patients is still unclear. Through the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases, the distinct expression of the TLR4 gene in 24 tumors and normal tissues was analyzed. Univariate Cox proportional hazards regression analysis was used to identify the cancer types whose TLR4 gene expression was related to prognosis. The relationship between TLR4 and tumor cell immune invasion was studied. Spearman’s rank correlation coefficient was used to analyze the relationship among TLR4 and immune neoantigens, tumor mutation burden (TMB), microsatellite instability (MSI), DNA repair genes, and DNA methylation. Gene Set Enrichment Analysis (GSEA) was used to identify the tumor-related pathways that the TLR4 gene was highly expressed in; the expression of the TLR4 gene was verified with the Human Protein Atlas (HPA) database. Low expression of TLR4 was associated with an inferior prognosis in kidney renal clear cell carcinoma (KIRC), skin cutaneous melanoma (SKCM), and uterine corpus endometrial carcinoma (UCEC), while high expression was related to a poor prognosis in head and neck squamous cell carcinoma (HNSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), and testicular germ cell tumor (TGCT). The expression of TLR4 was negatively correlated with the expression of B cells in STAD. The expression of TLR4 was positively correlated with the infiltration of B cells, CD4 and CD8 T cells, neutrophils, macrophages, and dendritic cells in STAD, KIRC, UCEC, TGCT, and SKCM. The expression of the TLR4 gene in KIRC, SKCM, STAD, TGCT, and UCEC was highly correlated with inducible T-cell costimulator (ICOS), cytotoxic T lymphocyte-associated molecule 4 (CTLA4), and CD28 immune checkpoints. Spearman’s rank correlation coefficient showed that the expression of TLR4 gene was significantly correlated with TMB in STAD and UCEC and was prominently correlated with MSI in TGCT, STAD, and SKCM. The expression of the TLR4 gene was highly correlated with MLH1, MSH2, and MSH6 in KIRC, SKCM, and STAD. The expression of the TLR4 gene was remarkably correlated with the methyltransferases DNA methyltransferase 2 (DNMT2) and DNA methyltransferase 3-beta (DNMT3B) in SKCM and STAD. Enrichment analysis showed that TLR4 was highly expressed in the chemokine signaling pathway and the cell adhesion molecule and cytokine receptor interaction pathway. In summary, the expression of TLR4 is linked to the prognosis of KIRC, SKCM, STAD, TGCT, and UCEC patients and the level of immune infiltration of CD4, CD8 T cells, macrophages, neutrophils, and dendritic cells.</p

Image_3_Differential Expression of the TLR4 Gene in Pan-Cancer and Its Related Mechanism.jpg

Previous studies have revealed the relationship between toll-like receptor 4 (TLR4) polymorphisms and cancer susceptibility. However, the relationship between TLR4 and prognosis and immune cell infiltration in pan-cancer patients is still unclear. Through the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases, the distinct expression of the TLR4 gene in 24 tumors and normal tissues was analyzed. Univariate Cox proportional hazards regression analysis was used to identify the cancer types whose TLR4 gene expression was related to prognosis. The relationship between TLR4 and tumor cell immune invasion was studied. Spearman’s rank correlation coefficient was used to analyze the relationship among TLR4 and immune neoantigens, tumor mutation burden (TMB), microsatellite instability (MSI), DNA repair genes, and DNA methylation. Gene Set Enrichment Analysis (GSEA) was used to identify the tumor-related pathways that the TLR4 gene was highly expressed in; the expression of the TLR4 gene was verified with the Human Protein Atlas (HPA) database. Low expression of TLR4 was associated with an inferior prognosis in kidney renal clear cell carcinoma (KIRC), skin cutaneous melanoma (SKCM), and uterine corpus endometrial carcinoma (UCEC), while high expression was related to a poor prognosis in head and neck squamous cell carcinoma (HNSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), and testicular germ cell tumor (TGCT). The expression of TLR4 was negatively correlated with the expression of B cells in STAD. The expression of TLR4 was positively correlated with the infiltration of B cells, CD4 and CD8 T cells, neutrophils, macrophages, and dendritic cells in STAD, KIRC, UCEC, TGCT, and SKCM. The expression of the TLR4 gene in KIRC, SKCM, STAD, TGCT, and UCEC was highly correlated with inducible T-cell costimulator (ICOS), cytotoxic T lymphocyte-associated molecule 4 (CTLA4), and CD28 immune checkpoints. Spearman’s rank correlation coefficient showed that the expression of TLR4 gene was significantly correlated with TMB in STAD and UCEC and was prominently correlated with MSI in TGCT, STAD, and SKCM. The expression of the TLR4 gene was highly correlated with MLH1, MSH2, and MSH6 in KIRC, SKCM, and STAD. The expression of the TLR4 gene was remarkably correlated with the methyltransferases DNA methyltransferase 2 (DNMT2) and DNA methyltransferase 3-beta (DNMT3B) in SKCM and STAD. Enrichment analysis showed that TLR4 was highly expressed in the chemokine signaling pathway and the cell adhesion molecule and cytokine receptor interaction pathway. In summary, the expression of TLR4 is linked to the prognosis of KIRC, SKCM, STAD, TGCT, and UCEC patients and the level of immune infiltration of CD4, CD8 T cells, macrophages, neutrophils, and dendritic cells.</p

Image_2_Differential Expression of the TLR4 Gene in Pan-Cancer and Its Related Mechanism.jpg

Previous studies have revealed the relationship between toll-like receptor 4 (TLR4) polymorphisms and cancer susceptibility. However, the relationship between TLR4 and prognosis and immune cell infiltration in pan-cancer patients is still unclear. Through the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases, the distinct expression of the TLR4 gene in 24 tumors and normal tissues was analyzed. Univariate Cox proportional hazards regression analysis was used to identify the cancer types whose TLR4 gene expression was related to prognosis. The relationship between TLR4 and tumor cell immune invasion was studied. Spearman’s rank correlation coefficient was used to analyze the relationship among TLR4 and immune neoantigens, tumor mutation burden (TMB), microsatellite instability (MSI), DNA repair genes, and DNA methylation. Gene Set Enrichment Analysis (GSEA) was used to identify the tumor-related pathways that the TLR4 gene was highly expressed in; the expression of the TLR4 gene was verified with the Human Protein Atlas (HPA) database. Low expression of TLR4 was associated with an inferior prognosis in kidney renal clear cell carcinoma (KIRC), skin cutaneous melanoma (SKCM), and uterine corpus endometrial carcinoma (UCEC), while high expression was related to a poor prognosis in head and neck squamous cell carcinoma (HNSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), and testicular germ cell tumor (TGCT). The expression of TLR4 was negatively correlated with the expression of B cells in STAD. The expression of TLR4 was positively correlated with the infiltration of B cells, CD4 and CD8 T cells, neutrophils, macrophages, and dendritic cells in STAD, KIRC, UCEC, TGCT, and SKCM. The expression of the TLR4 gene in KIRC, SKCM, STAD, TGCT, and UCEC was highly correlated with inducible T-cell costimulator (ICOS), cytotoxic T lymphocyte-associated molecule 4 (CTLA4), and CD28 immune checkpoints. Spearman’s rank correlation coefficient showed that the expression of TLR4 gene was significantly correlated with TMB in STAD and UCEC and was prominently correlated with MSI in TGCT, STAD, and SKCM. The expression of the TLR4 gene was highly correlated with MLH1, MSH2, and MSH6 in KIRC, SKCM, and STAD. The expression of the TLR4 gene was remarkably correlated with the methyltransferases DNA methyltransferase 2 (DNMT2) and DNA methyltransferase 3-beta (DNMT3B) in SKCM and STAD. Enrichment analysis showed that TLR4 was highly expressed in the chemokine signaling pathway and the cell adhesion molecule and cytokine receptor interaction pathway. In summary, the expression of TLR4 is linked to the prognosis of KIRC, SKCM, STAD, TGCT, and UCEC patients and the level of immune infiltration of CD4, CD8 T cells, macrophages, neutrophils, and dendritic cells.</p

Image_1_Differential Expression of the TLR4 Gene in Pan-Cancer and Its Related Mechanism.jpg

Previous studies have revealed the relationship between toll-like receptor 4 (TLR4) polymorphisms and cancer susceptibility. However, the relationship between TLR4 and prognosis and immune cell infiltration in pan-cancer patients is still unclear. Through the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases, the distinct expression of the TLR4 gene in 24 tumors and normal tissues was analyzed. Univariate Cox proportional hazards regression analysis was used to identify the cancer types whose TLR4 gene expression was related to prognosis. The relationship between TLR4 and tumor cell immune invasion was studied. Spearman’s rank correlation coefficient was used to analyze the relationship among TLR4 and immune neoantigens, tumor mutation burden (TMB), microsatellite instability (MSI), DNA repair genes, and DNA methylation. Gene Set Enrichment Analysis (GSEA) was used to identify the tumor-related pathways that the TLR4 gene was highly expressed in; the expression of the TLR4 gene was verified with the Human Protein Atlas (HPA) database. Low expression of TLR4 was associated with an inferior prognosis in kidney renal clear cell carcinoma (KIRC), skin cutaneous melanoma (SKCM), and uterine corpus endometrial carcinoma (UCEC), while high expression was related to a poor prognosis in head and neck squamous cell carcinoma (HNSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), and testicular germ cell tumor (TGCT). The expression of TLR4 was negatively correlated with the expression of B cells in STAD. The expression of TLR4 was positively correlated with the infiltration of B cells, CD4 and CD8 T cells, neutrophils, macrophages, and dendritic cells in STAD, KIRC, UCEC, TGCT, and SKCM. The expression of the TLR4 gene in KIRC, SKCM, STAD, TGCT, and UCEC was highly correlated with inducible T-cell costimulator (ICOS), cytotoxic T lymphocyte-associated molecule 4 (CTLA4), and CD28 immune checkpoints. Spearman’s rank correlation coefficient showed that the expression of TLR4 gene was significantly correlated with TMB in STAD and UCEC and was prominently correlated with MSI in TGCT, STAD, and SKCM. The expression of the TLR4 gene was highly correlated with MLH1, MSH2, and MSH6 in KIRC, SKCM, and STAD. The expression of the TLR4 gene was remarkably correlated with the methyltransferases DNA methyltransferase 2 (DNMT2) and DNA methyltransferase 3-beta (DNMT3B) in SKCM and STAD. Enrichment analysis showed that TLR4 was highly expressed in the chemokine signaling pathway and the cell adhesion molecule and cytokine receptor interaction pathway. In summary, the expression of TLR4 is linked to the prognosis of KIRC, SKCM, STAD, TGCT, and UCEC patients and the level of immune infiltration of CD4, CD8 T cells, macrophages, neutrophils, and dendritic cells.</p

Presentation_1_Differential Expression of the TLR4 Gene in Pan-Cancer and Its Related Mechanism.pdf

Previous studies have revealed the relationship between toll-like receptor 4 (TLR4) polymorphisms and cancer susceptibility. However, the relationship between TLR4 and prognosis and immune cell infiltration in pan-cancer patients is still unclear. Through the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases, the distinct expression of the TLR4 gene in 24 tumors and normal tissues was analyzed. Univariate Cox proportional hazards regression analysis was used to identify the cancer types whose TLR4 gene expression was related to prognosis. The relationship between TLR4 and tumor cell immune invasion was studied. Spearman’s rank correlation coefficient was used to analyze the relationship among TLR4 and immune neoantigens, tumor mutation burden (TMB), microsatellite instability (MSI), DNA repair genes, and DNA methylation. Gene Set Enrichment Analysis (GSEA) was used to identify the tumor-related pathways that the TLR4 gene was highly expressed in; the expression of the TLR4 gene was verified with the Human Protein Atlas (HPA) database. Low expression of TLR4 was associated with an inferior prognosis in kidney renal clear cell carcinoma (KIRC), skin cutaneous melanoma (SKCM), and uterine corpus endometrial carcinoma (UCEC), while high expression was related to a poor prognosis in head and neck squamous cell carcinoma (HNSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), and testicular germ cell tumor (TGCT). The expression of TLR4 was negatively correlated with the expression of B cells in STAD. The expression of TLR4 was positively correlated with the infiltration of B cells, CD4 and CD8 T cells, neutrophils, macrophages, and dendritic cells in STAD, KIRC, UCEC, TGCT, and SKCM. The expression of the TLR4 gene in KIRC, SKCM, STAD, TGCT, and UCEC was highly correlated with inducible T-cell costimulator (ICOS), cytotoxic T lymphocyte-associated molecule 4 (CTLA4), and CD28 immune checkpoints. Spearman’s rank correlation coefficient showed that the expression of TLR4 gene was significantly correlated with TMB in STAD and UCEC and was prominently correlated with MSI in TGCT, STAD, and SKCM. The expression of the TLR4 gene was highly correlated with MLH1, MSH2, and MSH6 in KIRC, SKCM, and STAD. The expression of the TLR4 gene was remarkably correlated with the methyltransferases DNA methyltransferase 2 (DNMT2) and DNA methyltransferase 3-beta (DNMT3B) in SKCM and STAD. Enrichment analysis showed that TLR4 was highly expressed in the chemokine signaling pathway and the cell adhesion molecule and cytokine receptor interaction pathway. In summary, the expression of TLR4 is linked to the prognosis of KIRC, SKCM, STAD, TGCT, and UCEC patients and the level of immune infiltration of CD4, CD8 T cells, macrophages, neutrophils, and dendritic cells.</p

Image_4_Differential Expression of the TLR4 Gene in Pan-Cancer and Its Related Mechanism.jpg

Previous studies have revealed the relationship between toll-like receptor 4 (TLR4) polymorphisms and cancer susceptibility. However, the relationship between TLR4 and prognosis and immune cell infiltration in pan-cancer patients is still unclear. Through the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases, the distinct expression of the TLR4 gene in 24 tumors and normal tissues was analyzed. Univariate Cox proportional hazards regression analysis was used to identify the cancer types whose TLR4 gene expression was related to prognosis. The relationship between TLR4 and tumor cell immune invasion was studied. Spearman’s rank correlation coefficient was used to analyze the relationship among TLR4 and immune neoantigens, tumor mutation burden (TMB), microsatellite instability (MSI), DNA repair genes, and DNA methylation. Gene Set Enrichment Analysis (GSEA) was used to identify the tumor-related pathways that the TLR4 gene was highly expressed in; the expression of the TLR4 gene was verified with the Human Protein Atlas (HPA) database. Low expression of TLR4 was associated with an inferior prognosis in kidney renal clear cell carcinoma (KIRC), skin cutaneous melanoma (SKCM), and uterine corpus endometrial carcinoma (UCEC), while high expression was related to a poor prognosis in head and neck squamous cell carcinoma (HNSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), and testicular germ cell tumor (TGCT). The expression of TLR4 was negatively correlated with the expression of B cells in STAD. The expression of TLR4 was positively correlated with the infiltration of B cells, CD4 and CD8 T cells, neutrophils, macrophages, and dendritic cells in STAD, KIRC, UCEC, TGCT, and SKCM. The expression of the TLR4 gene in KIRC, SKCM, STAD, TGCT, and UCEC was highly correlated with inducible T-cell costimulator (ICOS), cytotoxic T lymphocyte-associated molecule 4 (CTLA4), and CD28 immune checkpoints. Spearman’s rank correlation coefficient showed that the expression of TLR4 gene was significantly correlated with TMB in STAD and UCEC and was prominently correlated with MSI in TGCT, STAD, and SKCM. The expression of the TLR4 gene was highly correlated with MLH1, MSH2, and MSH6 in KIRC, SKCM, and STAD. The expression of the TLR4 gene was remarkably correlated with the methyltransferases DNA methyltransferase 2 (DNMT2) and DNA methyltransferase 3-beta (DNMT3B) in SKCM and STAD. Enrichment analysis showed that TLR4 was highly expressed in the chemokine signaling pathway and the cell adhesion molecule and cytokine receptor interaction pathway. In summary, the expression of TLR4 is linked to the prognosis of KIRC, SKCM, STAD, TGCT, and UCEC patients and the level of immune infiltration of CD4, CD8 T cells, macrophages, neutrophils, and dendritic cells.</p