Assessing the structural and interaction behaviour of Pr@Gd2O3 nanoparticles with biological entities

Aim: To facilitate researchers and practitioners for unveiling the mysterious functional aspects of human cellular system through performing exploratory searching on semantically integrated heterogeneous and geographically dispersed omics annotations. Background: Improving health standards of life is one of the motives which continuously instigates researchers and practitioners to strive for uncovering the mysterious aspects of human cellular system. Inferring new knowledge from known facts always requires reasonably large amount of data in well-structured, integrated and unified form. Due to the advent of especially high throughput and sensor technologies, biological data is growing heterogeneously and geographically at astronomical rate. Several data integration systems have been deployed to cope with the issues of data heterogeneity and global dispersion. Systems based on semantic data integration models are more flexible and expandable than syntax-based ones but still lack aspect-based data integration, persistence and querying. Furthermore, these systems do not fully support to warehouse biological entities in the form of semantic associations as naturally possessed by the human cell. Objective: To develop aspect-oriented formal data integration model for semantically integrating heterogeneous and geographically dispersed omics annotations for providing exploratory querying on integrated data. Method: We propose an aspect-oriented formal data integration model which uses web semantics standards to formally specify its each construct. Proposed model supports aspect-oriented representation of biological entities while addressing the issues of data heterogeneity and global dispersion. It associates and warehouses biological entities in the way they relate with Result: To show the significance of proposed model, we developed a data warehouse and information retrieval system based on proposed model compliant multi-layered and multi-modular software architecture. Results show that our model supports well for gathering, associating, integrating, persisting and querying each entity with respect to its all possible aspects within or across the various associated omics layers. Conclusion: Formal specifications better facilitate for addressing data integration issues by providing formal means for understanding omics data based on meaning instead of syntax

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Water Pollution and Its Impact on Environment of Society

International Research Journal of Management IT and Social Sciences ◽

10.21744/irjmis.v3i5.10 ◽

2016 ◽

Vol 3 (5) ◽

Author(s):

N. Thyagaraju

Keyword(s):

Water Pollution ◽

Pollution Prevention ◽

Human Beings ◽

Individual Level ◽

The Public ◽

The Government ◽

Living Organisms ◽

Set Up ◽

Biological Entities ◽

Micro Organisms

The present seminar paper mainly highlight the concept of water pollution, causes of water pollution, Its Effects, Elements of pollutants, Methods used to prevent the water pollution in environment and the mandatory initiatives taken by the concerned authorities for prevention of water pollution. Water is essential for survival of all living organisms on the earth. Thus for human beings and plants to survive on land, water should be easily accessible. The term “Pollution” is generally refers to addition of any foreign body either living or non – living or deletion of anything that naturally exists. The basic Sources of Water pollution causes due to Culmination into lakes, rivers, ponds, seas, oceans etc. Domestic drainage and sanitary waste, Industrial drainage and sewage, Industrial waste from factories, Dumping of domestic garbage, Immersion of Idols made of plaster of Paris, Excess use of Insecticides , pesticides, fungicides, Chemical fertilizers, Soil erosion during heavy rains and floods, Natural disasters, tsunami etc. General pollutants which are also caused for water pollution which include Organic, Inorganic, and Biological entities, Insecticides, Pesticides, Disinfectants ,Detergents, Industrial solvents, Acids, Ammonia fertilizers, heavy metals, Harmful bacteria, Virus, Micro –Organisms and worms, Toxic chemicals. Agricultural lands become infertile and thereby production also drops, Spread of epidemic diseases like Cholera, Dysentery, Typhoid, Diarrhea, Hepatitis, Jaundice etc. The basic responsibility of the Government, NGOs, National Pioneer scientific Research Institutions may conduct research oriented programs on control of water pollution by create awareness among the public through mass media and Environmental Education on recycling units, and water treatment plants must be established both at domestic levels and Industry levels, Every citizen must feel responsible to control water pollution. There have been many water pollution prevention acts that have been set up by the governments of the world. But these are not enough for permanent water pollution solutions. Each of us needs to take up the responsibility and do something at an everyday at individual level. Otherwise we can’t survive in a society forever in a future.

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Structure Unveils Relationships between RNA Virus Polymerases

Viruses ◽

10.3390/v13020313 ◽

2021 ◽

Vol 13 (2) ◽

pp. 313

Author(s):

Heli A. M. Mönttinen ◽

Janne J. Ravantti ◽

Minna M. Poranen

Keyword(s):

Phylogenetic Tree ◽

Rna Viruses ◽

Rna Virus ◽

Sequence Similarity ◽

Protein Structures ◽

Structural Similarity ◽

Functional Differentiation ◽

Comparison Method ◽

Homologous Structure ◽

Biological Entities

RNA viruses are the fastest evolving known biological entities. Consequently, the sequence similarity between homologous viral proteins disappears quickly, limiting the usability of traditional sequence-based phylogenetic methods in the reconstruction of relationships and evolutionary history among RNA viruses. Protein structures, however, typically evolve more slowly than sequences, and structural similarity can still be evident, when no sequence similarity can be detected. Here, we used an automated structural comparison method, homologous structure finder, for comprehensive comparisons of viral RNA-dependent RNA polymerases (RdRps). We identified a common structural core of 231 residues for all the structurally characterized viral RdRps, covering segmented and non-segmented negative-sense, positive-sense, and double-stranded RNA viruses infecting both prokaryotic and eukaryotic hosts. The grouping and branching of the viral RdRps in the structure-based phylogenetic tree follow their functional differentiation. The RdRps using protein primer, RNA primer, or self-priming mechanisms have evolved independently of each other, and the RdRps cluster into two large branches based on the used transcription mechanism. The structure-based distance tree presented here follows the recently established RdRp-based RNA virus classification at genus, subfamily, family, order, class and subphylum ranks. However, the topology of our phylogenetic tree suggests an alternative phylum level organization.

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Toward a Coronavirus Knowledge Graph

Genes ◽

10.3390/genes12070998 ◽

2021 ◽

Vol 12 (7) ◽

pp. 998

Author(s):

Peng Zhang ◽

Yi Bu ◽

Peng Jiang ◽

Xiaowen Shi ◽

Bing Lun ◽

...

Keyword(s):

Drug Discovery ◽

Angiotensin Converting Enzyme ◽

Information Sources ◽

Knowledge Graph ◽

Converting Enzyme ◽

Related Information ◽

Relationship Types ◽

Entity Disambiguation ◽

Public Datasets ◽

Biological Entities

This study builds a coronavirus knowledge graph (KG) by merging two information sources. The first source is Analytical Graph (AG), which integrates more than 20 different public datasets related to drug discovery. The second source is CORD-19, a collection of published scientific articles related to COVID-19. We combined both chemo genomic entities in AG with entities extracted from CORD-19 to expand knowledge in the COVID-19 domain. Before populating KG with those entities, we perform entity disambiguation on CORD-19 collections using Wikidata. Our newly built KG contains at least 21,700 genes, 2500 diseases, 94,000 phenotypes, and other biological entities (e.g., compound, species, and cell lines). We define 27 relationship types and use them to label each edge in our KG. This research presents two cases to evaluate the KG’s usability: analyzing a subgraph (ego-centered network) from the angiotensin-converting enzyme (ACE) and revealing paths between biological entities (hydroxychloroquine and IL-6 receptor; chloroquine and STAT1). The ego-centered network captured information related to COVID-19. We also found significant COVID-19-related information in top-ranked paths with a depth of three based on our path evaluation.

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Design strategy of ultrasmall Gd2O3 nanoparticles for T1 MRI with high performance

New Journal of Chemistry ◽

10.1039/d1nj00508a ◽

2021 ◽

Author(s):

Jianfeng Yang ◽

Pengyuan Shan ◽

Qingling Zhao ◽

Shuquan Zhang ◽

Lanlan Li ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

High Performance ◽

Design Strategy ◽

Resonance Imaging ◽

Relative Time ◽

Time Parameters ◽

Gd2o3 Nanoparticles

It is still a big challenge for designing Gd3+ based nanoparticles (NPs) for T1 MRI (Magnetic Resonance Imaging) with high performance and clarifying the effects of relative time parameters for...

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Exploitation of Marine-Derived Robust Biological Molecules to Manage Inflammatory Bowel Disease

Marine Drugs ◽

10.3390/md19040196 ◽

2021 ◽

Vol 19 (4) ◽

pp. 196

Author(s):

Muhammad Bilal ◽

Leonardo Vieira Nunes ◽

Marco Thúlio Saviatto Duarte ◽

Luiz Fernando Romanholo Ferreira ◽

Renato Nery Soriano ◽

...

Keyword(s):

Inflammatory Bowel Disease ◽

Bioactive Compounds ◽

Bowel Disease ◽

Clinical Translation ◽

Biologically Active ◽

Naturally Occurring ◽

Inflammatory Bowel ◽

Functional Features ◽

Biological Entities ◽

The Impact

Naturally occurring biological entities with extractable and tunable structural and functional characteristics, along with therapeutic attributes, are of supreme interest for strengthening the twenty-first-century biomedical settings. Irrespective of ongoing technological and clinical advancement, traditional medicinal practices to address and manage inflammatory bowel disease (IBD) are inefficient and the effect of the administered therapeutic cues is limited. The reasonable immune response or invasion should also be circumvented for successful clinical translation of engineered cues as highly efficient and robust bioactive entities. In this context, research is underway worldwide, and researchers have redirected or regained their interests in valorizing the naturally occurring biological entities/resources, for example, algal biome so-called “treasure of untouched or underexploited sources”. Algal biome from the marine environment is an immense source of excellence that has also been demonstrated as a source of bioactive compounds with unique chemical, structural, and functional features. Moreover, the molecular modeling and synthesis of new drugs based on marine-derived therapeutic and biological cues can show greater efficacy and specificity for the therapeutics. Herein, an effort has been made to cover the existing literature gap on the exploitation of naturally occurring biological entities/resources to address and efficiently manage IBD. Following a brief background study, a focus was given to design characteristics, performance evaluation of engineered cues, and point-of-care IBD therapeutics of diverse bioactive compounds from the algal biome. Noteworthy potentialities of marine-derived biologically active compounds have also been spotlighted to underlying the impact role of bio-active elements with the related pathways. The current review is also focused on the applied standpoint and clinical translation of marine-derived bioactive compounds. Furthermore, a detailed overview of clinical applications and future perspectives are also given in this review.

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A Detailed Catalogue of Multi-Omics Methodologies for Identification of Putative Biomarkers and Causal Molecular Networks in Translational Cancer Research

International Journal of Molecular Sciences ◽

10.3390/ijms22062822 ◽

2021 ◽

Vol 22 (6) ◽

pp. 2822

Author(s):

Efstathios Iason Vlachavas ◽

Jonas Bohn ◽

Frank Ückert ◽

Sylvia Nürnberg

Keyword(s):

Cancer Research ◽

Clinical Information ◽

Disease Diagnosis ◽

Molecular Data ◽

Molecular Networks ◽

Biological Knowledge ◽

Omics Data ◽

Translational Cancer Research ◽

Using Data ◽

Biological Entities

Recent advances in sequencing and biotechnological methodologies have led to the generation of large volumes of molecular data of different omics layers, such as genomics, transcriptomics, proteomics and metabolomics. Integration of these data with clinical information provides new opportunities to discover how perturbations in biological processes lead to disease. Using data-driven approaches for the integration and interpretation of multi-omics data could stably identify links between structural and functional information and propose causal molecular networks with potential impact on cancer pathophysiology. This knowledge can then be used to improve disease diagnosis, prognosis, prevention, and therapy. This review will summarize and categorize the most current computational methodologies and tools for integration of distinct molecular layers in the context of translational cancer research and personalized therapy. Additionally, the bioinformatics tools Multi-Omics Factor Analysis (MOFA) and netDX will be tested using omics data from public cancer resources, to assess their overall robustness, provide reproducible workflows for gaining biological knowledge from multi-omics data, and to comprehensively understand the significantly perturbed biological entities in distinct cancer types. We show that the performed supervised and unsupervised analyses result in meaningful and novel findings.

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