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Cloud technology is broadly supported by healthcare organizations worldwide. Throughout the previous few years, healthcare industries have recognized the potential of cloud computing architecture and how it can assistance them to give quality services to patients. The cloud technology has faster the way healthcare industry can use or share information crossways a network. This paper offering an e-health solution founded on healthcare information systems joined with cloud computing concept emphasis on medical information processing. Our proposed work based on public cloud and request management application has been proposed and analysed in terms of waiting time defined as Quality of Service criteria (QoS). The service of the public cloud has been modelled using queueing theory as two serially connected queues (Tandem Queues) M/M/s and single server retrial queue (SSRQ). The results obtained in our proposed model are considerably reducing the total waiting time of different class of units in the cloud system than the existing system and more utilization of service in cloud. [ABSTRACT FROM AUTHOR]

Histone H3 lysine 4 (H3K4) methylation is a dynamic modification. In budding yeast, H3K4 methylation is catalyzed by the Set1-COMPASS methyltransferase complex and is removed by Jhd2, a JMJC domain family demethylase. The catalytic JmjC and JmjN domains of Jhd2 have the ability to remove all three degrees (mono-, di-, and tri-) of H3K4 methylation. Jhd2 also contains a plant homeodomain (PHD) finger required for its chromatin association and H3K4 demethylase functions. The Jhd2 PHD finger associates with chromatin independent of H3K4 methylation and the H3 N-terminal tail. Therefore, how Jhd2 associates with chromatin to perform H3K4 demethylation has remained unknown. We report a novel interaction between the Jhd2 PHD finger and histone H2A. Two residues in H2A (Phe-26 and Glu-57) serve as a binding site for Jhd2 in vitro and mediate its chromatin association and H3K4 demethylase functions in vivo. Using RNA sequencing, we have identified the functional target genes for Jhd2 and theH2APhe-26 and Glu-57 residues.Wedemonstrate thatH2APhe-26 and Glu-57 residues control chromatin association and H3K4 demethylase functions of Jhd2 during positive or negative regulation of transcription at target genes. Importantly, we show that H2B Lys-123 ubiquitination blocks Jhd2 from accessing its binding site on chromatin, and thereby, we have uncovered a second mechanism by which H2B ubiquitination contributes to the trans-histone regulation of H3K4 methylation. Overall, our study provides novel insights into the chromatin binding dynamics and H3K4 demethylase functions of Jhd2. [ABSTRACT FROM AUTHOR]

Background: Nuclear-derived cell-free DNA (cfDNA) molecules in blood plasma are nonrandomly fragmented, bearing a wealth of information related to tissues of origin. DNASE1L3 (deoxyribonuclease 1 like 3) is an important player in shaping the fragmentation of nuclear-derived cfDNA molecules, preferentially generating molecules with 5 CC dinucleotide termini (i.e., 5 CC-end motif). However, the fragment end properties of microbial cfDNA and its clinical implication remain to be explored., Methods: We performed end motif analysis on microbial cfDNA fragments in plasma samples from patients with sepsis. A sequence context-based normalization method was used to minimize the potential biases for end motif analysis., Results: The end motif profiles of microbial cfDNA appeared to resemble that of nuclear cfDNA (Spearman correlation coefficient: 0.82, P value 0.001). The CC-end motif was the most preferred end motif in microbial cfDNA, suggesting that DNASE1L3 might also play a role in the fragmentation of microbe-derived cfDNA in plasma. Of note, differential end motifs were present between microbial cfDNA originating from infection-causing pathogens (enriched at the CC-end) and contaminating microbial DNA potentially derived from reagents or the environment (nearly random). The use of fragment end signatures allowed differentiation between confirmed pathogens and contaminating microbes, with an area under the receiver operating characteristic curve of 0.99. The performance appeared to be superior to conventional analysis based on microbial cfDNA abundance alone., Conclusions: The use of fragmentomic features could facilitate the differentiation of underlying contaminating microbes from true pathogens in sepsis. This work demonstrates the potential usefulness of microbial cfDNA fragmentomics in metagenomics analysis., (© American Association for Clinical Chemistry 2022.)