• Genomics & Informatics
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• 제19권4호
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• pp.44.1-44.9
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• 2021

Autism is a complex neurodevelopmental disorder, the prevalence of which has increased drastically in India in recent years. Neuroligin is a type I transmembrane protein that plays a crucial role in synaptogenesis. Alterations in synaptic genes are most commonly implicated in autism and other cognitive disorders. The present study investigated the neuroligin 3 gene in the Indian autistic population by sequencing and in silico pathogenicity prediction of molecular changes. In total, 108 clinically described individuals with autism were included from the North Karnataka region of India, along with 150 age-, sex-, and ethnicity-matched healthy controls. Genomic DNA was extracted from peripheral blood, and exonic regions were sequenced. The functional and structural effects of variants of the neuroligin 3 protein were predicted. One coding sequence variant (a missense variant) and four non-coding variants (two 5'-untranslated region [UTR] variants and two 3'-UTR variants) were recorded. The novel missense variant was found in 25% of the autistic population. The C/C genotype of c.551T>C was significantly more common in autistic children than in controls (p = 0.001), and a significantly increased risk of autism (24.7-fold) was associated with this genotype (p = 0.001). The missense variant showed pathogenic effects and high evolutionary conservation over the functions of the neuroligin 3 protein. In the present study, we reported a novel missense variant, V184A, which causes abnormal neuroligin 3 and was found with high frequency in the Indian autistic population. Therefore, neuroligin is a candidate gene for future molecular investigations and functional analysis in the Indian autistic population.

• 대한본초학회지
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• 제39권3호
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• pp.37-47
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• 2024

Objectives : Because predicting the potential efficacy and mechanisms of Korean medicines is challenging due to their high complexity, employing an approach based on network pharmacology could be effective. In this study, network pharmacological analysis was utilized to anticipate the effects of YunPye-Hwan (YPH) in treating Chronic obstructive pulmonary disease (COPD). Methods : Compounds and their related target genes of YPH were gathered from the TCMSP and PubChem databases. These target genes of YPH were subsequently compared with gene sets associated with COPD to assess correlation. Next, core genes were identified through a two-step screening process, and finally, functional enrichment analysis of these core genes was conducted using both Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways. Results : A total of 15 compounds and 437 target genes were gathered, resulting in a network comprising 473 nodes and 14,137 edges. Among them, 276 genes overlapped with gene sets associated with COPD, indicating a significant correlation between YPH and COPD. Functional enrichment analysis of the 18 core genes revealed biological processes and pathways such as "miRNA Transcription," "Nucleic Acid-Templated Transcription," "DNA-binding Transcription Factor Activity," "MAPK signaling pathway," and "TNF signaling pathway" were implicated. Conclusion : YPH exhibited significant relevance to COPD by modulating cell proliferation, differentiation, inflammation, and cell death pathways. This study could serve as a foundational framework for further research investigating the potential use of YPH in the treatment of COPD.

• Geomechanics and Engineering
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• 제37권1호
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• pp.65-72
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• 2024

Water ingress poses a common and intricate geological hazard with profound implications for tunnel construction's speed and safety. The project's success hinges significantly on the precision of estimating water inflow during excavation, a critical factor in early-stage decision-making during conception and design. This article introduces an optimized model employing the gene expression programming (GEP) approach to forecast tunnel water inflow. The GEP model was refined by developing an equation that best aligns with predictive outcomes. The equation's outputs were compared with measured data and assessed against practical scenarios to validate its potential applicability in calculating tunnel water input. The optimized GEP model excelled in forecasting tunnel water inflow, outperforming alternative machine learning algorithms like SVR, GPR, DT, and KNN. This positions the GEP model as a leading choice for accurate and superior predictions. A state-of-the-art machine learning-based graphical user interface (GUI) was innovatively crafted for predicting and visualizing tunnel water inflow. This cutting-edge tool leverages ML algorithms, marking a substantial advancement in tunneling prediction technologies, providing accuracy and accessibility in water inflow projections.

• Biomolecules & Therapeutics
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• 제26권3호
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• pp.282-289
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• 2018

Melanin is a pigment produced from tyrosine in melanocytes. Although melanin has a protective role against UVB radiation-induced damage, it is also associated with the development of melanoma and darker skin tone. Tyrosinase is a key enzyme in melanin synthesis, which regulates the rate-limiting step during conversion of tyrosine into DOPA and dopaquinone. To develop effective RNA interference therapeutics, we designed a melanin siRNA pool by applying multiple prediction programs to reduce human tyrosinase levels. First, 272 siRNAs passed the target accessibility evaluation using the RNAxs program. Then we selected 34 siRNA sequences with ${\Delta}G{\geq}-34.6kcal/mol$, i-Score value ${\geq}65$, and siRNA scales score ${\leq}30$. siRNAs were designed as 19-bp RNA duplexes with an asymmetric 3' overhang at the 3' end of the antisense strand. We tested if these siRNAs effectively reduced tyrosinase gene expression using qRT-PCR and found that 17 siRNA sequences were more effective than commercially available siRNA. Three siRNAs further tested showed an effective visual color change in MNT-1 human cells without cytotoxic effects, indicating these sequences are anti-melanogenic. Our study revealed that human tyrosinase siRNAs could be efficiently designed using multiple prediction algorithms.

• Genomics & Informatics
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• 제4권2호
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• pp.71-76
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• 2006

We have investigated biological responses to radiofrequency (RF) radiation in in vitro and in vivo models. By measuring the levels of heat shock proteins as well as the activation of mitogen activated protein kinases (MAPKs), we could not detect any differences upon RF exposure. In this study, we used more sensitive method to find the molecular responses to RF radiation. Jurkat, human T-Iymphocyte cells were exposed to 1763 MHz RF radiation at an average specific absorption rate (SAR) of 10 W/kg for one hour and harvested immediately (R0) or after five hours (R5). From the profiles of 30,000 genes, we selected 68 differentially expressed genes among sham (S), R0 and R5 groups using a random-variance F-test. Especially 45 annotated genes were related to metabolism, apoptosis or transcription regulation. Based on support vector machine (SVM) algorithm, we designed prediction model using 68 genes to discriminate three groups. Our prediction model could predict the target class of 19 among 20 examples exactly (95% accuracy). From these data, we could select the 68 biomarkers to predict the RF radiation exposure with high accuracy, which might need to be validated in in vivo models.

• Geomechanics and Engineering
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• 제36권5호
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• pp.489-509
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• 2024

Slope stability analysis and prediction are of critical importance to geotechnical engineers, given the severe consequences associated with slope failure. This research endeavors to forecast the factor of safety (FOS) for slopes through the implementation of six distinct ML techniques, including back propagation neural networks (BPNN), feed-forward neural networks (FFNN), Takagi-Sugeno fuzzy system (TSF), gene expression programming (GEP), and least-square support vector machine (Ls-SVM). 344 slope cases were analyzed, incorporating a variety of geometric and shear strength parameters measured through the PLAXIS software alongside several loss functions to assess the models' performance. The findings demonstrated that all models produced satisfactory results, with BPNN and GEP models proving to be the most precise, achieving an R² of 0.86 each and MAE and MAPE rates of 0.00012 and 0.00002 and 0.005 and 0.004, respectively. A Pearson correlation and residuals statistical analysis were carried out to examine the importance of each factor in the prediction, revealing that all considered geomechanical features are significantly relevant to slope stability. However, the parameters of friction angle and slope height were found to be the most and least significant, respectively. In addition, to aid in the FOS computation for engineering challenges, a graphical user interface (GUI) for the ML-based techniques was created.

• Journal of Microbiology
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• 제44권1호
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• pp.64-71
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• 2006

To investigate the effects of the nucleotide sequences in Shine-Dalgarno (SD) and the spacer region (SD-ATG) on bovine growth hormone (bGH) gene expression, the expression vectors under the control of the T7 promoter (pT7-7 vector) were constructed using bGH derivatives (bGH1 & bGH14) which have different 5'-coding regions and were induced in E. coli BL21 (DE3). Oligonucleotides containing random SD sequences and a spacer region were chemically synthesized and the distance between the SD region and the initiation codon were fixed to nine bases in length. The oligonucleotides were annealed and fused to the bGH1 and bGH14 cDNA, respectively. When the bGH gene was induced with IPTG in E. coli BL21(DE3), some clones containing only bGH14 cDNA produced considerable levels of bGH in the range of $6.9\%\;to\;8.5\%$ of total cell proteins by SDS-PAGE and Western blot. Otherwise, the bGH was not detected in any clones with bGH1 cDNA. Accordingly, the nucleotide sequences of SD and the spacer region affect on bGH expression indicates that the sequences sufficiently destabilize the mRNA secondary structure of the bGH14 gene. When the free energy was calculated from the transcription initiation site to the +51 nucleotide of bGH cDNA using a program of nucleic acid folding and hybridization prediction, the constructs with values below -26.3 kcal/mole (toward minus direction) were not expressed. The constructs with the original sequence of bGH cDNA also did not show any expression, regardless of the free energy values. Thus, the disruption of the mRNA secondary structure may be a major factor regulating bGH expression in the translation initiation process. Accordingly, the first stem-loop among two secondary structures present in the 5'-end region of the bGH gene should be disrupted for the effective expression of bGH.

• Asian-Australasian Journal of Animal Sciences
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• 제32권12호
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• pp.1942-1949
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• 2019

Objective: Leukocyte cell-derived chemotaxin 2 (LECT2) is associated with several physiological processes including inflammation, tumorigenesis, and natural killer T cell generation. Chicken LECT2 (chLECT2) gene was originally identified as one of the differentially expressed genes in chicken kidney tissue, where the chickens were fed with different calcium doses. In this study, the molecular characteristics and gene expression of chLECT2 were analyzed under the stimulation of toll-like receptor 3 (TLR3) ligand to understand the involvement of chLECT2 expression in chicken metabolic disorders. Methods: Amino acid sequence of LECT2 proteins from various species including fowl, fish, and mammal were retrieved from the Ensembl database and subjected to Insilco analyses. In addition, the time- and dose-dependent expression of chLECT2 was examined in DF-1 cells which were stimulated with polyinosinic:polycytidylic acid (poly [I:C]), a TLR3 ligand. Further, to explore the transcription factors required for the transcription of chLECT2, DF-1 cells were treated with poly (I:C) in the presence or absence of the nuclear factor ${\kappa}B$ ($NF{\kappa}B$) and activated protein 1 (AP-1) inhibitors. Results: The amino acid sequence prediction of chLECT2 protein revealed that along with duck LECT2 (duLECT2), it has unique signal peptide different from other vertebrate orthologs, and only chLECT2 and duLECT2 have an additional 157 and 161 amino acids on their carboxyl terminus, respectively. Phylogenetic analysis suggested that chLECT2 is evolved from a common ancestor along with the actinopterygii hence, more closely related than to the mammals. Our quantitative polymerase chain reaction results showed that, the expression of chLECT2 was up-regulated significantly in DF-1 cells under the stimulation of poly (I:C) (p<0.05). However, in the presence of $NF{\kappa}B$ or AP-1 inhibitors, the expression of chLECT2 is suppressed suggesting that both $NF{\kappa}B$ and AP-1 transcription factors are required for the induction of chLECT2 expression. Conclusion: The present results suggest that chLECT2 gene might be a target gene of TLR3 signaling. For the future, the expression pattern or molecular mechanism of chLECT2 under stimulation of other innate immune receptors shall be studied. The protein function of chLECT2 will be more clearly understood if further investigation about the mechanism of LECT2 in TLR pathways is conducted.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2005년도 생물공학의 동향(XVI)
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• pp.427-427
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• 2005

• Journal of Microbiology and Biotechnology
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• 제11권1호
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• pp.164-166
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• 2001

To examine the characteristics of the recombinant thin aggregative fimbriae of Salmonella, the AgfA subunit gene was amplified from Salmonella enteritidis using a PCR. The maltose binding protein (MBP)-AgfA fusion protein was overproduced in E. coli and purified. The secondary structure of AgfA was then elucidated from the difference CD spectra. An estimation of the secondary structure of AgfA using the self-consistent method revealed a mostly ${\beta}-sheet$ structure.