THE INTELLECTUAL STRUCTURE OF ELECTRONIC RECORDS MANAGEMENT

A number of countries have launched projects with a particular emphasis on using information technologies (IT) to provide electronic information and services to citizens and businesses. Through various IT, tremendous amount of electronic records in government agencies are created. These records and archives are the basis of knowledge management. Electronic records management (ERM) is a fast growing field throughout the last decades. Theoretical foundations for ERM have remained obscure from the research community. To map the intellectual structure of ERM research, this study identifies the high-impact articles as well as the correlations among these scholar publications. In this study, co-citation, co-word, association rule and cluster analysis techniques are used to investigate the intellectual pillars of the ERM literature. This study exposes researchers to a new way of profiling knowledge networks and their relationships the area of ERM, thereby helping academia and practitioners better understand contemporary studies. The results of the mapping can help identify the research direction of ERM research, provide a valuable tool for researchers to access ERM literature, and acts as an exemplary model for future researches

Experimental maps of DNA structure at nucleotide resolution distinguish intrinsic from protein-induced DNA deformations

Recognition of DNA by proteins depends on DNA sequence and structure. Often unanswered is whether the structure of naked DNA persists in a protein–DNA complex, or whether protein binding changes DNA shape. While X-ray structures of protein–DNA complexes are numerous, the structure of naked cognate DNA is seldom available experimentally. We present here an experimental and computational analysis pipeline that uses hydroxyl radical cleavage to map, at single-nucleotide resolution, DNA minor groove width, a recognition feature widely exploited by proteins. For 11 protein–DNA complexes, we compared experimental maps of naked DNA minor groove width with minor groove width measured from X-ray co-crystal structures. Seven sites had similar minor groove widths as naked DNA and when bound to protein. For four sites, part of the DNA in the complex had the same structure as naked DNA, and part changed structure upon protein binding. We compared the experimental map with minor groove patterns of DNA predicted by two computational approaches, DNAshape and ORChID2, and found good but not perfect concordance with both. This experimental approach will be useful in mapping structures of DNA sequences for which high-resolution structural data are unavailable. This approach allows probing of protein family-dependent readout mechanisms.National Institutes of Health [R01GM106056 to R.R., T.D.T.; U54CA121852 in part to T.D.T.]; Boston University Undergraduate Research Opportunities Program [Faculty Matching Grants to D.O. and Y.J.]; USC Graduate School [Research Enhancement Fellowship and Manning Endowed Fellowship to T.P.C.]. R.R. is an Alfred P. Sloan Research Fellow. Funding for open access charge: Boston University. (R01GM106056 - National Institutes of Health; U54CA121852 - National Institutes of Health; Boston University Undergraduate Research Opportunities Program; USC Graduate School; Boston University)https://academic.oup.com/nar/article/46/5/2636/4829691?searchresult=1https://academic.oup.com/nar/article/46/5/2636/4829691?searchresult=1Published versio

Systematic prediction of DNA shape changes due to CpG methylation explains epigenetic effects on protein–DNA binding

Background DNA shape analysis has demonstrated the potential to reveal structure-based mechanisms of protein–DNA binding. However, information about the influence of chemical modification of DNA is limited. Cytosine methylation, the most frequent modification, represents the addition of a methyl group at the major groove edge of the cytosine base. In mammalian genomes, cytosine methylation most frequently occurs at CpG dinucleotides. In addition to changing the chemical signature of C/G base pairs, cytosine methylation can affect DNA structure. Since the original discovery of DNA methylation, major efforts have been made to understand its effect from a sequence perspective. Compared to unmethylated DNA, however, little structural information is available for methylated DNA, due to the limited number of experimentally determined structures. To achieve a better mechanistic understanding of the effect of CpG methylation on local DNA structure, we developed a high-throughput method, methyl-DNAshape, for predicting the effect of cytosine methylation on DNA shape. Results Using our new method, we found that CpG methylation significantly altered local DNA shape. Four DNA shape features—helix twist, minor groove width, propeller twist, and roll—were considered in this analysis. Distinct distributions of effect size were observed for different features. Roll and propeller twist were the DNA shape features most strongly affected by CpG methylation with an effect size depending on the local sequence context. Methylation-induced changes in DNA shape were predictive of the measured rate of cleavage by DNase I and suggest a possible mechanism for some of the methylation sensitivities that were recently observed for human Pbx-Hox complexes. Conclusions CpG methylation is an important epigenetic mark in the mammalian genome. Understanding its role in protein–DNA recognition can further our knowledge of gene regulation. Our high-throughput methyl-DNAshape method can be used to predict the effect of cytosine methylation on DNA shape and its subsequent influence on protein–DNA interactions. This approach overcomes the limited availability of experimental DNA structures that contain 5-methylcytosine

Empagliflozin Protects HK-2 Cells from High Glucose-Mediated Injuries via a Mitochondrial Mechanism

Empagliflozin is known to retard the progression of kidney disease in diabetic patients. However, the underlying mechanism is incompletely understood. High glucose induces oxidative stress in renal tubules, eventually leading to mitochondrial damage. Here, we investigated whether empagliflozin exhibits protective functions in renal tubules via a mitochondrial mechanism. We used human proximal tubular cell (PTC) line HK-2 and employed western blotting, terminal deoxynucleotidyl transferase dUTP nick end labelling assay, fluorescence staining, flow cytometry, and enzyme-linked immunosorbent assay to investigate the impact of high glucose and empagliflozin on cellular apoptosis, mitochondrial morphology, and functions including mitochondrial membrane potential (MMP), reactive oxygen species (ROS) production, and adenosine triphosphate (ATP) generation. We found that PTCs were susceptible to high glucose-induced mitochondrial fragmentation, and empagliflozin ameliorated this effect via the regulation of mitochondrial fission (FIS1 and DRP1) and fusion (MFN1 and MFN2) proteins. Empagliflozin reduced the high glucose-induced cellular apoptosis and improved mitochondrial functions by restoring mitochondrial ROS production, MMP, and ATP generation. Our results suggest that empagliflozin may protect renal PTCs from high glucose-mediated injuries through a mitochondrial mechanism. This could be one of the novel mechanisms explaining the benefits demonstrated in EMPA-REG OUTCOME trial

Predicting DNA structure using a deep learning method

Abstract Understanding the mechanisms of protein-DNA binding is critical in comprehending gene regulation. Three-dimensional DNA structure, also described as DNA shape, plays a key role in these mechanisms. In this study, we present a deep learning-based method, Deep DNAshape, that fundamentally changes the current k-mer based high-throughput prediction of DNA shape features by accurately accounting for the influence of extended flanking regions, without the need for extensive molecular simulations or structural biology experiments. By using the Deep DNAshape method, DNA structural features can be predicted for any length and number of DNA sequences in a high-throughput manner, providing an understanding of the effects of flanking regions on DNA structure in a target region of a sequence. The Deep DNAshape method provides access to the influence of distant flanking regions on a region of interest. Our findings reveal that DNA shape readout mechanisms of a core target are quantitatively affected by flanking regions, including extended flanking regions, providing valuable insights into the detailed structural readout mechanisms of protein-DNA binding. Furthermore, when incorporated in machine learning models, the features generated by Deep DNAshape improve the model prediction accuracy. Collectively, Deep DNAshape can serve as versatile and powerful tool for diverse DNA structure-related studies

DNAshapeR: An R/Bioconductor package for DNA shape prediction and feature encoding

DNAshapeR predicts DNA shape features in an ultra-fast, high-throughput manner from genomic sequencing data. The package takes either nucleotide sequence or genomic coordinates as input and generates various graphical representations for visualization and further analysis. DNAshapeR further encodes DNA sequence and shape features as user-defined combinations of k-mer and DNA shape features. The resulting feature matrices can be readily used as input of various machine learning software packages for further modeling studies.ISSN:1367-4803ISSN:1460-205

Probing the role of a minor groove-linker histidine in Exd-Hox–DNA binding through molecular dynamics simulation

Molecular dynamics simulation protocols for Gromacs 2020.3 and binding free energy input files for g_mmpbsa</p