Scores of given alternatives.

Scores of given alternatives.</p

Order through 2TLNNs operators.

Order through 2TLNNs operators.</p

Image1_Risk model of hepatocellular carcinoma based on cuproptosis-related genes.JPEG

Background: Owing to the heterogeneity displayed by hepatocellular carcinoma (HCC) and the complexity of tumor microenvironment (TME), it is noted that the long-term effectiveness of the cancer therapy poses a severe clinical challenge. Hence, it is essential to categorize and alter the treatment intervention decisions for these tumors.Materials and methods: “ConsensusClusterPlus” tool was used for developing a secure molecular classification system that was based on the cuproptosis-linked gene expression. Furthermore, all clinical properties, pathway characteristics, genomic changes, and immune characteristics of different cell types involved in the immune pathways were also assessed. Univariate Cox regression and the least absolute shrinkage and selection operator (Lasso) analyses were used for designing the prognostic risk model associated with cuproptosis.Results: Three cuproptosis-linked subtypes (clust1, clust2, and clust3) were detected. Out of these, Clust3 showed the worst prognosis, followed by clust2, while Clust1 showed the best prognosis. Three subtypes had significantly different enrichment in pathways related to Tricarboxylic Acid (TCA) cycle, cell cycle, and cell senescence (p Conclusion: Three new molecular subgroups based on cuproptosis-linked genes were revealed, and a cuproptosis-related prognostic risk model comprising seven genes was established in this study, which could assist in predicting the prognosis and identifying the patients benefit from immunotherapy.</p

Image3_Risk model of hepatocellular carcinoma based on cuproptosis-related genes.JPEG

Background: Owing to the heterogeneity displayed by hepatocellular carcinoma (HCC) and the complexity of tumor microenvironment (TME), it is noted that the long-term effectiveness of the cancer therapy poses a severe clinical challenge. Hence, it is essential to categorize and alter the treatment intervention decisions for these tumors.Materials and methods: “ConsensusClusterPlus” tool was used for developing a secure molecular classification system that was based on the cuproptosis-linked gene expression. Furthermore, all clinical properties, pathway characteristics, genomic changes, and immune characteristics of different cell types involved in the immune pathways were also assessed. Univariate Cox regression and the least absolute shrinkage and selection operator (Lasso) analyses were used for designing the prognostic risk model associated with cuproptosis.Results: Three cuproptosis-linked subtypes (clust1, clust2, and clust3) were detected. Out of these, Clust3 showed the worst prognosis, followed by clust2, while Clust1 showed the best prognosis. Three subtypes had significantly different enrichment in pathways related to Tricarboxylic Acid (TCA) cycle, cell cycle, and cell senescence (p Conclusion: Three new molecular subgroups based on cuproptosis-linked genes were revealed, and a cuproptosis-related prognostic risk model comprising seven genes was established in this study, which could assist in predicting the prognosis and identifying the patients benefit from immunotherapy.</p

Exploratory Study on Th1 Epitope-Induced Protective Immunity against <i>Coxiella burnetii</i> Infection

<div><p><i>Coxiella burnetii</i> is a Gram-negative bacterium that causes Q fever in humans. In the present study, 131 candidate peptides were selected from the major immunodominant proteins (MIPs) of <i>C. burnetii</i> due to their high-affinity binding capacity for the MHC class II molecule H2 I-A^b based on bioinformatic analyses. Twenty-two of the candidate peptides with distinct MIP epitopes were well recognized by the IFN-γ recall responses of CD4⁺ T cells from mice immunized with parental proteins in an ELISPOT assay. In addition, 7 of the 22 peptides could efficiently induce CD4⁺ T cells from mice immunized with <i>C. burnetii</i> to rapidly proliferate and significantly increase IFN-γ production. Significantly higher levels of IL-2, IL-12p70, IFN-γ, and TNF-α were also detected in serum from mice immunized with a pool of the 7 peptides. Immunization with the pool of 7 peptides, but not the individual peptides, conferred a significant protection against <i>C. burnetii</i> infection in mice, suggesting that these Th1 peptides could work together to efficiently activate CD4⁺ T cells to produce the Th1-type immune response against <i>C. burnetii</i> infection. These observations could contribute to the rational design of molecular vaccines for Q fever.</p></div

Biotinylated surface-exposed proteins of <i>R. rickettsii</i> analyzed by ESI-MS/MS.

a<p>The National Center for Biotechnology Information (NCBI, <a href="http://www.ncbi.nlm.nih.gov/" target="_blank">http://www.ncbi.nlm.nih.gov/</a>). Data were retrieved on March 4, 2013.</p>b<p>The signal peptide was predicted using SignalP 4.1 web server (<a href="http://www.cbs.dtu.dk/services/SignalP/" target="_blank">http://www.cbs.dtu.dk/services/SignalP/</a>). Websites were accessed on March 4, 2013.</p>c<p>The transmembrane strands and the topology of beta-barrel outer membrane proteins of <i>R. rickettsii</i> were predicted using the PRED-TMBB web server (<a href="http://bioinformatics.biol.uoa.gr/PRED-TMBB" target="_blank">http://bioinformatics.biol.uoa.gr/PRED-TMBB</a>), which is based on a Hidden Markov Model, trained according to the Conditional Maximum Likelihood criterion. A score less than 2.965 indicated that the protein may be a membrane protein. Data were retrieved on March 7, 2013.</p>d<p>The ions score is presented as -10*Log (P), where P is the probability that the observed match is a random event. Individual ions scores >54 indicate identity or extensive homology (<i>P</i><0.05). Protein scores are derived from ions scores on a non-probabilistic basis for ranking protein hits.</p>e<p>The Pfam-A was used to predict the family of the protein, Pfam does not allow any amino-acid to match more than one Pfam-A family(<a href="http://pfam.sanger.ac.uk/" target="_blank">http://pfam.sanger.ac.uk/</a>), unless the overlapping families are part of the same clan. In cases where two members of the same clan match the same region of a sequence, only one match is show, that with the lowest E-value. The E-value cut-off in Pfam-A search was set to 1.0. Data were retrieved on July 19, 2013.</p

Table1_Risk model of hepatocellular carcinoma based on cuproptosis-related genes.DOCX

Background: Owing to the heterogeneity displayed by hepatocellular carcinoma (HCC) and the complexity of tumor microenvironment (TME), it is noted that the long-term effectiveness of the cancer therapy poses a severe clinical challenge. Hence, it is essential to categorize and alter the treatment intervention decisions for these tumors.Materials and methods: “ConsensusClusterPlus” tool was used for developing a secure molecular classification system that was based on the cuproptosis-linked gene expression. Furthermore, all clinical properties, pathway characteristics, genomic changes, and immune characteristics of different cell types involved in the immune pathways were also assessed. Univariate Cox regression and the least absolute shrinkage and selection operator (Lasso) analyses were used for designing the prognostic risk model associated with cuproptosis.Results: Three cuproptosis-linked subtypes (clust1, clust2, and clust3) were detected. Out of these, Clust3 showed the worst prognosis, followed by clust2, while Clust1 showed the best prognosis. Three subtypes had significantly different enrichment in pathways related to Tricarboxylic Acid (TCA) cycle, cell cycle, and cell senescence (p Conclusion: Three new molecular subgroups based on cuproptosis-linked genes were revealed, and a cuproptosis-related prognostic risk model comprising seven genes was established in this study, which could assist in predicting the prognosis and identifying the patients benefit from immunotherapy.</p

Immunoprotection against <i>C. burnetii</i> induced by the adoptive transfer of Coxiella-specific CD4⁺ T cells.

<p>CD4⁺ T cells from <i>C. burnetii</i> WCA-immunized mice were transferred to groups of six naïve mice, and each mouse was challenged with <i>C. burnetii</i> 24 h post-transfer. On day 7 after challenge, the mice were sacrificed and their spleens were harvested for the detection of <i>C. burnetii</i> DNA by Qpcr (A) and measurement of spleen weights (B). Data are expressed as the mean of 6 mice, and error bars indicate the standard deviation. Compared with the negative control; *<i>P</i><0.05.</p

Image2_Risk model of hepatocellular carcinoma based on cuproptosis-related genes.JPEG

Background: Owing to the heterogeneity displayed by hepatocellular carcinoma (HCC) and the complexity of tumor microenvironment (TME), it is noted that the long-term effectiveness of the cancer therapy poses a severe clinical challenge. Hence, it is essential to categorize and alter the treatment intervention decisions for these tumors.Materials and methods: “ConsensusClusterPlus” tool was used for developing a secure molecular classification system that was based on the cuproptosis-linked gene expression. Furthermore, all clinical properties, pathway characteristics, genomic changes, and immune characteristics of different cell types involved in the immune pathways were also assessed. Univariate Cox regression and the least absolute shrinkage and selection operator (Lasso) analyses were used for designing the prognostic risk model associated with cuproptosis.Results: Three cuproptosis-linked subtypes (clust1, clust2, and clust3) were detected. Out of these, Clust3 showed the worst prognosis, followed by clust2, while Clust1 showed the best prognosis. Three subtypes had significantly different enrichment in pathways related to Tricarboxylic Acid (TCA) cycle, cell cycle, and cell senescence (p Conclusion: Three new molecular subgroups based on cuproptosis-linked genes were revealed, and a cuproptosis-related prognostic risk model comprising seven genes was established in this study, which could assist in predicting the prognosis and identifying the patients benefit from immunotherapy.</p

Table3_Risk model of hepatocellular carcinoma based on cuproptosis-related genes.DOCX

Background: Owing to the heterogeneity displayed by hepatocellular carcinoma (HCC) and the complexity of tumor microenvironment (TME), it is noted that the long-term effectiveness of the cancer therapy poses a severe clinical challenge. Hence, it is essential to categorize and alter the treatment intervention decisions for these tumors.Materials and methods: “ConsensusClusterPlus” tool was used for developing a secure molecular classification system that was based on the cuproptosis-linked gene expression. Furthermore, all clinical properties, pathway characteristics, genomic changes, and immune characteristics of different cell types involved in the immune pathways were also assessed. Univariate Cox regression and the least absolute shrinkage and selection operator (Lasso) analyses were used for designing the prognostic risk model associated with cuproptosis.Results: Three cuproptosis-linked subtypes (clust1, clust2, and clust3) were detected. Out of these, Clust3 showed the worst prognosis, followed by clust2, while Clust1 showed the best prognosis. Three subtypes had significantly different enrichment in pathways related to Tricarboxylic Acid (TCA) cycle, cell cycle, and cell senescence (p Conclusion: Three new molecular subgroups based on cuproptosis-linked genes were revealed, and a cuproptosis-related prognostic risk model comprising seven genes was established in this study, which could assist in predicting the prognosis and identifying the patients benefit from immunotherapy.</p