XRD data

XRD data of talc, TN 450, TN 550, and TN 65

BET and Pore size data

Nitrogen adsorption and desorption curves and pore size distribution of talc and TN 450, TN 550, and TN 65

Image3_Comprehensive analysis of histone methylation modification regulators for predicting prognosis and drug sensitivity in lung adenocarcinoma.TIF

Histone methylation is an epigenetic modification regulated by histone methyltransferases, histone demethylases, and histone methylation reader proteins that play important roles in the pathogenic mechanism of cancers. However, the prognostic value of histone methylation in lung adenocarcinoma (LUAD) remains unknown. Here, we found that LUAD cases could be divided into 2 subtypes by the 144 histone methylation modification regulators (HMMRs), with a significant difference in OS time. Ninety-five of the HMMRs were identified as differentially expressed genes (DEGs) between normal and tumor samples, and 13 of them were further discovered to be survival-related genes (SRGs). By applying the least absolute shrinkage and selector operator (LASSO) Cox regression, we constructed an 8-gene-based risk signature according to the TCGA (training) cohort, and the risk score calculated by the signature was proven to be an independent factor in both the training and validation cohorts. We then discovered that the immune functions were generally impaired in the high-risk groups defined by the HMMR signature (especially for the DCs and immune check-point pathway). Functional analyses showed that the DEGs between the low- and high-risk groups were related to the cell cycle. The drug sensitivity analysis indicated that our risk model could predict the sensitivity of commonly used drugs. Moreover, according to the DEGs between the low- and high-risk groups, we discovered several new compounds that showed potential therapeutic value for high-risk LUAD patients. In conclusion, our study demonstrated that HMMRs were promising predictors for the prognoses and drug therapeutic effects for LUAD patients.</p

<i>Galleria mellonella</i> as a model system to assess the efficacy of antimicrobial agents against <i>Klebsiella pneumoniae</i> infection

<i>Galleria mellonella</i> as a model system to assess the efficacy of antimicrobial agents against <i>Klebsiella pneumoniae</i> infectio

Image2_Comprehensive analysis of histone methylation modification regulators for predicting prognosis and drug sensitivity in lung adenocarcinoma.TIF

Histone methylation is an epigenetic modification regulated by histone methyltransferases, histone demethylases, and histone methylation reader proteins that play important roles in the pathogenic mechanism of cancers. However, the prognostic value of histone methylation in lung adenocarcinoma (LUAD) remains unknown. Here, we found that LUAD cases could be divided into 2 subtypes by the 144 histone methylation modification regulators (HMMRs), with a significant difference in OS time. Ninety-five of the HMMRs were identified as differentially expressed genes (DEGs) between normal and tumor samples, and 13 of them were further discovered to be survival-related genes (SRGs). By applying the least absolute shrinkage and selector operator (LASSO) Cox regression, we constructed an 8-gene-based risk signature according to the TCGA (training) cohort, and the risk score calculated by the signature was proven to be an independent factor in both the training and validation cohorts. We then discovered that the immune functions were generally impaired in the high-risk groups defined by the HMMR signature (especially for the DCs and immune check-point pathway). Functional analyses showed that the DEGs between the low- and high-risk groups were related to the cell cycle. The drug sensitivity analysis indicated that our risk model could predict the sensitivity of commonly used drugs. Moreover, according to the DEGs between the low- and high-risk groups, we discovered several new compounds that showed potential therapeutic value for high-risk LUAD patients. In conclusion, our study demonstrated that HMMRs were promising predictors for the prognoses and drug therapeutic effects for LUAD patients.</p

Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan-3

<p><b>Copyright information:</b></p><p>Taken from "Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan"</p><p>BMC Bioinformatics 2006;7():25-25.</p><p>Published online 18 Jan 2006</p><p>PMCID:PMC1382255.</p><p></p>ing a description of SNPs in regions of consecutive homozygous calls (i.e. LOH) in table form (A) or with a plot (B). Both panels are screen shots; the labels in B have been redrawn for clarity

Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan-4

<p><b>Copyright information:</b></p><p>Taken from "Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan"</p><p>BMC Bioinformatics 2006;7():25-25.</p><p>Published online 18 Jan 2006</p><p>PMCID:PMC1382255.</p><p></p>op row; case L99-2287), 3 (second row; case L99-2297) and 2 (third row), and uniparental isodisomy of chromosome 14 (fourth row; case X_1054). The x-axis spans chromosomes 1–22 and X. B. Detailed view of microdeletions on chromosome 3 (top row) and 2 (bottom row). The x-axis spans chromosomes 2 and 3

Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan-0

<p><b>Copyright information:</b></p><p>Taken from "Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan"</p><p>BMC Bioinformatics 2006;7():25-25.</p><p>Published online 18 Jan 2006</p><p>PMCID:PMC1382255.</p><p></p>g column headers with SNP identifiers and chromosomal position as well as SNP genotypes (AA, BB, AB, or NoCall), SNP copy number, and associated values. This text file is obtained as an output from the Affymetrix CNAT. The SNPscan website includes separate upload pages for additional SNP analysis tools

Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan-7

<p><b>Copyright information:</b></p><p>Taken from "Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan"</p><p>BMC Bioinformatics 2006;7():25-25.</p><p>Published online 18 Jan 2006</p><p>PMCID:PMC1382255.</p><p></p>16 of 23 cells revealed a deletion (an example is shown in A), while the remainder appeared euploid (B)

Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan-9

<p><b>Copyright information:</b></p><p>Taken from "Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan"</p><p>BMC Bioinformatics 2006;7():25-25.</p><p>Published online 18 Jan 2006</p><p>PMCID:PMC1382255.</p><p></p>air, and produces a third track in the form of a ratio plot (in logscale) comparing the two samples. This feature is useful for any paired samples such as SNP profiles in normal versus cancer tissue. In this example the genotype changes from homozygous to heterozygous were indicated in red, while other optional color displays were suppressed. This highlighted a region of chromosomal amplification