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Search results for: Achitphol Chookaew
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</div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Achitphol Chookaew</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Transcriptomics Analysis on Comparing Non-Small Cell Lung Cancer versus Normal Lung, and Early Stage Compared versus Late-Stages of Non-Small Cell Lung Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Achitphol%20Chookaew">Achitphol Chookaew</a>, <a href="https://publications.waset.org/search?q=Paramee%20Thongsukhsai"> Paramee Thongsukhsai</a>, <a href="https://publications.waset.org/search?q=Patamarerk%20Engsontia"> Patamarerk Engsontia</a>, <a href="https://publications.waset.org/search?q=Narongwit%20Nakwan"> Narongwit Nakwan</a>, <a href="https://publications.waset.org/search?q=Pritsana%20Raugrut"> Pritsana Raugrut</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Lung cancer is one of the most common malignancies and primary cause of death due to cancer worldwide. Non-small cell lung cancer (NSCLC) is the main subtype in which majority of patients present with advanced-stage disease. Herein, we analyzed differentially expressed genes to find potential biomarkers for lung cancer diagnosis as well as prognostic markers. We used transcriptome data from our 2 NSCLC patients and public data (GSE81089) composing of 8 NSCLC and 10 normal lung tissues. Differentially expressed genes (DEGs) between NSCLC and normal tissue and between early-stage and late-stage NSCLC were analyzed by the DESeq2. Pairwise correlation was used to find the DEGs with false discovery rate (FDR) adjusted p-value £ 0.05 and |log2 fold change| ³ 4 for NSCLC versus normal and FDR adjusted p-value £ 0.05 with |log2 fold change| ³ 2 for early versus late-stage NSCLC. Bioinformatic tools were used for functional and pathway analysis. Moreover, the top ten genes in each comparison group were verified the expression and survival analysis via GEPIA. We found 150 up-regulated and 45 down-regulated genes in NSCLC compared to normal tissues. Many immnunoglobulin-related genes e.g., IGHV4-4, IGHV5-10-1, IGHV4-31, IGHV4-61, and IGHV1-69D were significantly up-regulated. 22 genes were up-regulated, and five genes were down-regulated in late-stage compared to early-stage NSCLC. The top five DEGs genes were KRT6B, SPRR1A, KRT13, KRT6A and KRT5. Keratin 6B (KRT6B) was the most significantly increased gene in the late-stage NSCLC. From GEPIA analysis, we concluded that IGHV4-31 and IGKV1-9 might be used as diagnostic biomarkers, while KRT6B and KRT6A might be used as prognostic biomarkers. However, further clinical validation is needed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Bioinformatics" title="Bioinformatics">Bioinformatics</a>, <a href="https://publications.waset.org/search?q=differentially%20expressed%20genes" title=" differentially expressed genes"> differentially expressed genes</a>, <a href="https://publications.waset.org/search?q=non-small%20cell%20lung%20cancer" title=" non-small cell lung cancer"> non-small cell lung cancer</a>, <a href="https://publications.waset.org/search?q=transcriptomics." title=" transcriptomics."> transcriptomics.</a> </p> <a href="https://publications.waset.org/10011671/transcriptomics-analysis-on-comparing-non-small-cell-lung-cancer-versus-normal-lung-and-early-stage-compared-versus-late-stages-of-non-small-cell-lung-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10011671/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10011671/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10011671/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10011671/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10011671/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10011671/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10011671/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10011671/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10011671/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10011671/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10011671.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">897</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Ethyl Methane Sulfonate-Induced Dunaliella salina KU11 Mutants Affected for Growth Rate, Cell Accumulation and Biomass</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Vongsathorn%20Ngampuak">Vongsathorn Ngampuak</a>, <a href="https://publications.waset.org/search?q=Yutachai%20Chookaew"> Yutachai Chookaew</a>, <a href="https://publications.waset.org/search?q=Wipawee%20Dejtisakdi"> Wipawee Dejtisakdi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p><em>Dunaliella salina</em> has great potential as a system for generating commercially valuable products, including beta-carotene, pharmaceuticals, and biofuels. Our goal is to improve this potential by enhancing growth rate and other properties of <em>D. salina</em> under optimal growth conditions. We used ethyl methane sulfonate (EMS) to generate random mutants in <em>D. salina </em>KU11, a strain classified in Thailand. In a preliminary experiment, we first treated <em>D. salina</em> cells with 0%, 0.8%, 1.0%, 1.2%, 1.44% and 1.66% EMS to generate a killing curve. After that, we randomly picked 30 candidates from approximately 300 isolated survivor colonies from the 1.44% EMS treatment (which permitted 30% survival) as an initial test of the mutant screen. Among the 30 survivor lines, we found that 2 strains (mutant #17 and #24) had significantly improved growth rates and cell number accumulation at stationary phase approximately up to 1.8 and 1.45 fold, respectively, 2 strains (mutant #6 and #23) had significantly decreased growth rates and cell number accumulation at stationary phase approximately down to 1.4 and 1.35 fold, respectively, while 26 of 30 lines had similar growth rates compared with the wild type control. We also analyzed cell size for each strain and found there was no significant difference comparing all mutants with the wild type. In addition, mutant #24 had shown an increase of biomass accumulation approximately 1.65 fold compared with the wild type strain on day 5 that was entering early stationary phase. From these preliminary results, it could be feasible to identify <em>D. salina</em> mutants with significant improved growth rate, cell accumulation and biomass production compared to the wild type for the further study; this makes it possible to improve this microorganism as a platform for biotechnology application.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Dunaliella%20salina" title="Dunaliella salina">Dunaliella salina</a>, <a href="https://publications.waset.org/search?q=mutant" title=" mutant"> mutant</a>, <a href="https://publications.waset.org/search?q=ethyl%20methane%20sulfonate" title=" ethyl methane sulfonate"> ethyl methane sulfonate</a>, <a href="https://publications.waset.org/search?q=growth%20rate" title=" growth rate"> growth rate</a>, <a href="https://publications.waset.org/search?q=biomass." title=" biomass."> biomass.</a> </p> <a 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