Cancer screening is an important aspect of comprehensive health care, making a significant contribution to reducing the risk of death and the cost of treating patients. Finding new tumor markers with high sensitivity and specificity is a trend in the research activities in Vietnam as well as all over the world. Long interspersed element-1 (LINE-1), a large proportion of repeating DNA, is transposable to different positions in the genome. LINE-1 activity is controlled through DNA methylation (the CpG is attached with CH3), whereby LINE-1 is highly methylated in normal cells. However, in some types of cancer such as lung, breast, stomach, liver, rectum... changes in the methylation status LINE-1 have been noticed. To study the methylation status of the LINE-1 sequence, we used a quantitative methyl-specific PCR technique. This method requires a standard calibrator to quantify the rate of methylation. From the commercial methylated DNA (CpG Methylated Human Genomic DNA, Promega), we cloned two regions of the LINE-1 promoter corresponding to a reference sequence and an investigated one (target sequence) which are bisulfite transformed. As a result, we have created two recombinant plasmids, pRef-LINE1 and pMe-LINE1. The plasmids were mixed at 10% of methylation and could be used as a standard control for analyzing the DNA methylation of specimens from patients. Keywords: DNA methylation, DNA repeating sequence, LINE-1, quantitative methyl-specific-PCR (qMSP), tumor markers. References [1] A. P. Feinberg, Phenotypic Plasticity and the Epigenetics of Human Disease, Nature, Vol. 447, No. 7143, 2007, pp. 433-40, https://doi.org/10.1038/nature05919.[2] A. H. Ting, K. M. McGarvey, S. B. Baylin, The cancer Epigenome-Components and Functional Correlates, Genes Dev, Vol. 20, No. 23, 2006, pp. 3215-31, https://doi.org/10.1101/gad.1464906.[3] A. E. Teschendorff et al., DNA Methylation Outliers in Normal Breast Tissue Identify Field Defects that are Enriched in Cancer, Nat Commun, Vol. 7, No., 2016, pp. 10478, https://doi.org/10.1038/ncomms10478.[4] C. Leygo et al., DNA Methylation as a Noninvasive Epigenetic Biomarker for the Detection of Cancer, Dis Markers, Vol. 2017, No., 2017, pp. 3726595, https://doi.org/10.1155/2017/3726595.[5] X. Hao et al., DNA Methylation Markers for Diagnosis and Prognosis of Common Cancers, Proc Natl Acad Sci U S A, Vol. 114, No. 28, 2017, pp. 7414-7419, https://doi.org/10.1073/pnas.1703577114.[6] N. Kitkumthorn, A. Mutirangura, Long Interspersed Nuclear Element-1 Hypomethylation in Cancer: Biology and Clinical Applications, Clin Epigenetics, Vol. 2, No. 2, 2011, pp. 315-30, https://doi.org/10.1007/s13148-011-0032-8.[7] M. A. Kerachian, M. Kerachian, Long Interspersed Nucleotide Element-1 (LINE-1) Methylation in Colorectal Cancer, Clin Chim Acta, Vol. 488, No., 2019, pp. 209-214, https://doi.org/10.1016/j.cca.2018.11.018.[8] M. Barchitta et al., LINE-1 Hypermethylation in White Blood Cell DNA Is Associated with High-Grade Cervical Intraepithelial Neoplasia, BMC Cancer, Vol. 17, No. 1, 2017, pp. 601, https://doi.org/10.1186/s12885-017-3582-0.[9] Y. Baba et al., Long Interspersed Element-1 Methylation Level as a Prognostic Biomarker in Gastrointestinal Cancers, Digestion, Vol. 97, No. 1, 2018, pp. 26-30, https://doi.org/10.1159/000484104.[10] J. G. Herman et al., Methylation-specific PCR: a Novel PCR Assay for Methylation Status of Cpg Islands, Proc Natl Acad Sci U S A, Vol. 93, No. 18, 1996, pp. 9821-9826, https://doi.org/10.1073/pnas.93.18.9821.[11] K. Hattermann et al., A Methylation-Specific And SYBR-Green-Based Quantitative Polymerase Chain Reaction Technique for O6-Methylguanine DNA Methyltransferase Promoter Methylation Analysis, Anal Biochem, Vol. 377, No. 1, 2008, pp. 62-71, https://doi.org/10.1016/j.ab.2008.03.014. [12] K. J. Livak, T. D. Schmittgen, Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2(-Delta Delta C(T)) Method, Methods, Vol. 25, No. 4, 2001, pp. 402-408, https://doi.org/10.1006/meth.2001.1262.[13] Y. Hou et al., Serious Overestimation In Quantitative PCR By Circular (Supercoiled) Plasmid Standard: Microalgal Pcna As The Model Gene, PLoS One, Vol. 5, No. 3, 2010, pp. e9545, https://doi.org/10.1371/journal.pone.0009545.[14] G. Johnson, T. Nolan, S. A. Bustin, Real-time Quantitative PCR, Pathogen Detection and MIQE, Methods Mol Biol, Vol. 943, 2013, pp. 1-16, https://doi.org/10.1007/978-1-60327-353-4_1.

This paper is aimed at analysing the factors affecting individual customer satisfaction with the mobile banking service quality during Covid-19 period in Vietnam. The methodology applied including SERVQUAL model, using e-SQ scale with EFA model. Data were collected from 405 observations answered via online survey of individuals using mobile banking service in period Jan-March 2022. Key findings of the research include: First, five factors affecting the positive customer satisfactions on mobile banking are ranked from highest to lowest impacts includes: Covid-19 pandemic, security, convenience/utility, empathy and responsiveness, and service fees. Second, Covid-19 pandemic provided the great opportunity for expanding mobile banking services, and Vietnamese banks have utilized this opportunity well by applying various promotion policies for encouraging more clients using mobile banking services. The digital transformation of banks enhances this process well. Third, the younger people have more satisfactions on mobile banking compared to older people, as the old have some difficulties in adapting to technological devices and softwares. Some recommendations have been proposed to improve the quality of mobile banking services for the new normal post-covid 19 pandemic period. Keywords: service quality, Covid-19, mobile banking, individual customers, satisfaction..