Bayesian Look Ahead Sampling Methods to Allocate up to M Observations among k Populations

In this paper, we study the Bayesian look ahead sampling methods for allocating up to M observations among k populations to select the best population(s). First, we investigated the properties of fixed sample-size sampling algorithm proposed by Professor Klaus J. Miescke, which always draws fixed number of observations at the next step. Then we proposed and studied a m-truncated sampling algorithm, which draws up to m observations sequentially. Based on these two algorithms, respectively, two Bayesian look-ahead sampling methods for allocating up to M observations among k populations are developed. To investigate the properties of and compare these two methods, we implement them to allocate up to M observations among k normal distributions with the same variance or k binomial populations to select the best population. For given values of M, the Bayes risks of these two methods are calculated or estimated. The smaller the Bayes risk, the better the method. It turns out that when the sampling cost is large compared with the decision loss, the second method is better than the first. When the sampling cost is not very large, then in the normal case the two methods are comparable, with one method occasionally better than the other. On the other hand, in the binomial case, the second method dominates most of the time. These two methods are then applied in various other situations

Table2_The hypoxia-related signature predicts prognosis, pyroptosis and drug sensitivity of osteosarcoma.docx

Osteosarcoma (OS) is one of the most common types of solid sarcoma with a poor prognosis. Solid tumors are often exposed to hypoxic conditions, while hypoxia is regarded as a driving force in tumor recurrence, metastasis, progression, low chemosensitivity and poor prognosis. Pytoptosis is a gasdermin-mediated inflammatory cell death that plays an essential role in host defense against tumorigenesis. However, few studies have reported relationships among hypoxia, pyroptosis, tumor immune microenvironment, chemosensitivity, and prognosis in OS. In this study, gene and clinical data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases were merged to develop a hypoxia risk model comprising four genes (PDK1, LOX, DCN, and HMOX1). The high hypoxia risk group had a poor prognosis and immunosuppressive status. Meanwhile, the infiltration of CD8+ T cells, activated memory CD4+ T cells, and related chemokines and genes were associated with clinical survival outcomes or chemosensitivity, the possible crucial driving forces of the OS hypoxia immune microenvironment that affect the development of pyroptosis. We established a pyroptosis risk model based on 14 pyroptosis-related genes to independently predict not only the prognosis but also the chemotherapy sensitivities. By exploring the various connections between the hypoxic immune microenvironment and pyroptosis, this study indicates that hypoxia could influence tumor immune microenvironment (TIM) remodeling and promote pyroptosis leading to poor prognosis and low chemosensitivity.</p

Image2_The hypoxia-related signature predicts prognosis, pyroptosis and drug sensitivity of osteosarcoma.TIF

Osteosarcoma (OS) is one of the most common types of solid sarcoma with a poor prognosis. Solid tumors are often exposed to hypoxic conditions, while hypoxia is regarded as a driving force in tumor recurrence, metastasis, progression, low chemosensitivity and poor prognosis. Pytoptosis is a gasdermin-mediated inflammatory cell death that plays an essential role in host defense against tumorigenesis. However, few studies have reported relationships among hypoxia, pyroptosis, tumor immune microenvironment, chemosensitivity, and prognosis in OS. In this study, gene and clinical data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases were merged to develop a hypoxia risk model comprising four genes (PDK1, LOX, DCN, and HMOX1). The high hypoxia risk group had a poor prognosis and immunosuppressive status. Meanwhile, the infiltration of CD8+ T cells, activated memory CD4+ T cells, and related chemokines and genes were associated with clinical survival outcomes or chemosensitivity, the possible crucial driving forces of the OS hypoxia immune microenvironment that affect the development of pyroptosis. We established a pyroptosis risk model based on 14 pyroptosis-related genes to independently predict not only the prognosis but also the chemotherapy sensitivities. By exploring the various connections between the hypoxic immune microenvironment and pyroptosis, this study indicates that hypoxia could influence tumor immune microenvironment (TIM) remodeling and promote pyroptosis leading to poor prognosis and low chemosensitivity.</p

Image3_The hypoxia-related signature predicts prognosis, pyroptosis and drug sensitivity of osteosarcoma.TIFF

Osteosarcoma (OS) is one of the most common types of solid sarcoma with a poor prognosis. Solid tumors are often exposed to hypoxic conditions, while hypoxia is regarded as a driving force in tumor recurrence, metastasis, progression, low chemosensitivity and poor prognosis. Pytoptosis is a gasdermin-mediated inflammatory cell death that plays an essential role in host defense against tumorigenesis. However, few studies have reported relationships among hypoxia, pyroptosis, tumor immune microenvironment, chemosensitivity, and prognosis in OS. In this study, gene and clinical data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases were merged to develop a hypoxia risk model comprising four genes (PDK1, LOX, DCN, and HMOX1). The high hypoxia risk group had a poor prognosis and immunosuppressive status. Meanwhile, the infiltration of CD8+ T cells, activated memory CD4+ T cells, and related chemokines and genes were associated with clinical survival outcomes or chemosensitivity, the possible crucial driving forces of the OS hypoxia immune microenvironment that affect the development of pyroptosis. We established a pyroptosis risk model based on 14 pyroptosis-related genes to independently predict not only the prognosis but also the chemotherapy sensitivities. By exploring the various connections between the hypoxic immune microenvironment and pyroptosis, this study indicates that hypoxia could influence tumor immune microenvironment (TIM) remodeling and promote pyroptosis leading to poor prognosis and low chemosensitivity.</p

Table1_The hypoxia-related signature predicts prognosis, pyroptosis and drug sensitivity of osteosarcoma.docx

Osteosarcoma (OS) is one of the most common types of solid sarcoma with a poor prognosis. Solid tumors are often exposed to hypoxic conditions, while hypoxia is regarded as a driving force in tumor recurrence, metastasis, progression, low chemosensitivity and poor prognosis. Pytoptosis is a gasdermin-mediated inflammatory cell death that plays an essential role in host defense against tumorigenesis. However, few studies have reported relationships among hypoxia, pyroptosis, tumor immune microenvironment, chemosensitivity, and prognosis in OS. In this study, gene and clinical data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases were merged to develop a hypoxia risk model comprising four genes (PDK1, LOX, DCN, and HMOX1). The high hypoxia risk group had a poor prognosis and immunosuppressive status. Meanwhile, the infiltration of CD8+ T cells, activated memory CD4+ T cells, and related chemokines and genes were associated with clinical survival outcomes or chemosensitivity, the possible crucial driving forces of the OS hypoxia immune microenvironment that affect the development of pyroptosis. We established a pyroptosis risk model based on 14 pyroptosis-related genes to independently predict not only the prognosis but also the chemotherapy sensitivities. By exploring the various connections between the hypoxic immune microenvironment and pyroptosis, this study indicates that hypoxia could influence tumor immune microenvironment (TIM) remodeling and promote pyroptosis leading to poor prognosis and low chemosensitivity.</p

Image5_The hypoxia-related signature predicts prognosis, pyroptosis and drug sensitivity of osteosarcoma.TIF

Osteosarcoma (OS) is one of the most common types of solid sarcoma with a poor prognosis. Solid tumors are often exposed to hypoxic conditions, while hypoxia is regarded as a driving force in tumor recurrence, metastasis, progression, low chemosensitivity and poor prognosis. Pytoptosis is a gasdermin-mediated inflammatory cell death that plays an essential role in host defense against tumorigenesis. However, few studies have reported relationships among hypoxia, pyroptosis, tumor immune microenvironment, chemosensitivity, and prognosis in OS. In this study, gene and clinical data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases were merged to develop a hypoxia risk model comprising four genes (PDK1, LOX, DCN, and HMOX1). The high hypoxia risk group had a poor prognosis and immunosuppressive status. Meanwhile, the infiltration of CD8+ T cells, activated memory CD4+ T cells, and related chemokines and genes were associated with clinical survival outcomes or chemosensitivity, the possible crucial driving forces of the OS hypoxia immune microenvironment that affect the development of pyroptosis. We established a pyroptosis risk model based on 14 pyroptosis-related genes to independently predict not only the prognosis but also the chemotherapy sensitivities. By exploring the various connections between the hypoxic immune microenvironment and pyroptosis, this study indicates that hypoxia could influence tumor immune microenvironment (TIM) remodeling and promote pyroptosis leading to poor prognosis and low chemosensitivity.</p

Image1_The hypoxia-related signature predicts prognosis, pyroptosis and drug sensitivity of osteosarcoma.TIF

Osteosarcoma (OS) is one of the most common types of solid sarcoma with a poor prognosis. Solid tumors are often exposed to hypoxic conditions, while hypoxia is regarded as a driving force in tumor recurrence, metastasis, progression, low chemosensitivity and poor prognosis. Pytoptosis is a gasdermin-mediated inflammatory cell death that plays an essential role in host defense against tumorigenesis. However, few studies have reported relationships among hypoxia, pyroptosis, tumor immune microenvironment, chemosensitivity, and prognosis in OS. In this study, gene and clinical data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases were merged to develop a hypoxia risk model comprising four genes (PDK1, LOX, DCN, and HMOX1). The high hypoxia risk group had a poor prognosis and immunosuppressive status. Meanwhile, the infiltration of CD8+ T cells, activated memory CD4+ T cells, and related chemokines and genes were associated with clinical survival outcomes or chemosensitivity, the possible crucial driving forces of the OS hypoxia immune microenvironment that affect the development of pyroptosis. We established a pyroptosis risk model based on 14 pyroptosis-related genes to independently predict not only the prognosis but also the chemotherapy sensitivities. By exploring the various connections between the hypoxic immune microenvironment and pyroptosis, this study indicates that hypoxia could influence tumor immune microenvironment (TIM) remodeling and promote pyroptosis leading to poor prognosis and low chemosensitivity.</p

Image4_The hypoxia-related signature predicts prognosis, pyroptosis and drug sensitivity of osteosarcoma.TIFF

Osteosarcoma (OS) is one of the most common types of solid sarcoma with a poor prognosis. Solid tumors are often exposed to hypoxic conditions, while hypoxia is regarded as a driving force in tumor recurrence, metastasis, progression, low chemosensitivity and poor prognosis. Pytoptosis is a gasdermin-mediated inflammatory cell death that plays an essential role in host defense against tumorigenesis. However, few studies have reported relationships among hypoxia, pyroptosis, tumor immune microenvironment, chemosensitivity, and prognosis in OS. In this study, gene and clinical data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases were merged to develop a hypoxia risk model comprising four genes (PDK1, LOX, DCN, and HMOX1). The high hypoxia risk group had a poor prognosis and immunosuppressive status. Meanwhile, the infiltration of CD8+ T cells, activated memory CD4+ T cells, and related chemokines and genes were associated with clinical survival outcomes or chemosensitivity, the possible crucial driving forces of the OS hypoxia immune microenvironment that affect the development of pyroptosis. We established a pyroptosis risk model based on 14 pyroptosis-related genes to independently predict not only the prognosis but also the chemotherapy sensitivities. By exploring the various connections between the hypoxic immune microenvironment and pyroptosis, this study indicates that hypoxia could influence tumor immune microenvironment (TIM) remodeling and promote pyroptosis leading to poor prognosis and low chemosensitivity.</p

Anomalous Frictional Behaviors of Ir and Au Tips Sliding on Graphene/Ni(111) Substrate: Density Functional Theory Calculations

The atomic force microscope (AFM) provides a facilitating tool to investigate the atomic-scale friction properties of surfaces through the sliding of the scanning tip; therefore, the interaction between the tip and the surface should play an important role to determine the frictional behaviors. In this study, density functional theory (DFT) calculations have been carried out to perform the pushing down processes of a tip (10 atom Ir or Au tip) on the top, hollow, and bridge sites of the graphene/Ni(111) substrate. The calculation results indicate that the interactions between the tips and the graphene/Ni(111) substrate influence the adsorption energy remarkably, leading to the sequence of bridge < top < hollow for Ir and Au tips, which is totally different from the adsorption energy of an inert Ar atom, following the sequence of hollow < bridge < top. The strong interactions between the (Ir or Au) tip and the graphene/Ni(111) substrate will introduce novel frictional properties into the system, and an anomalous negative friction coefficient could be obtained. Further investigations show that these interactions arise from the hybridizations between the 2p_<i>z</i> orbitals of C atoms and the 5d_<i>z</i>² orbitals of the tip apex atom

Oxidized Low-Density Lipoprotein Suppresses Expression of Prostaglandin E Receptor Subtype EP3 in Human THP-1 Macrophages

<div><p>EP3, one of four prostaglandin E2 (PGE2) receptors, is significantly lower in atherosclerotic plaques than in normal arteries and is localized predominantly in macrophages of the plaque shoulder region. However, mechanisms behind this EP3 expression pattern are still unknown. We investigated the underlying mechanism of EP3 expression in phorbol 12-myristate 13-acetate (PMA)-differentiated THP-1 macrophages with oxidized low-density lipoprotein (oxLDL) treatment. We found that oxLDL decreased EP3 expression, in a dose-dependent manner, at both the mRNA and protein levels. Moreover, oxLDL inhibited nuclear factor-κB (NF-κB)-dependent transcription of the EP3 gene by the activation of peroxisome proliferator-activated receptor-γ (PPAR-γ). Finally, chromatin immunoprecipitation revealed decreased binding of NF-κB to the EP3 promoter with oxLDL and PPAR-γ agonist treatment. Our results show that oxLDL suppresses EP3 expression by activation of PPAR-γ and subsequent inhibition of NF-κB in macrophages. These results suggest that down-regulation of EP3 expression by oxLDL is associated with impairment of EP3-mediated anti-inflammatory effects, and that EP3 receptor activity may exert a beneficial effect on atherosclerosis.</p></div