scholarly journals CRISPR-Cas9 sgRNA design and outcome assessment: Bioinformatics tools and aquaculture applications

2021 ◽  
Author(s):  
Mingkun Luo ◽  
Jun Wang ◽  
Zaijie Dong ◽  
Chenghui Wang ◽  
Guoqing Lu
Keyword(s):  
Outcome Assessment ◽  
Bioinformatics Tools ◽  
Sgrna Design

Quick Consult: Quick Consult: Acromioplasty

2002 ◽  
Vol 7 (3) ◽  
pp. 4-5
Keyword(s):  
Glasgow Coma Scale ◽  
Outcome Assessment ◽  
High Probability ◽  
Vegetative State ◽  
Behavioral Impairment ◽  
Whole Person ◽  
Ordinal Scales ◽  
Probability Of Death ◽  
The Individual ◽  
Assessment Scales

Abstract Different jurisdictions use the AMA Guides to the Evaluation of Permanent Impairment (AMA Guides) for different purposes, and this article reviews a specific jurisdictional definition in the Province of Ontario of catastrophic impairment that incorporates the AMA Guides. In Ontario, a whole person impairment (WPI) exceeding 54% or a mental or behavioral impairment of Class 4 or 5 qualifies the individual for catastrophic benefits, and individuals who do not meet the test receive a lesser benefit. By inference, this establishes a parity threshold among dissimilar injuries and dissimilar outcome assessment scales for benefits. In Ontario, the Glasgow Coma Scale (GCS) identifies patients who have a high probability of death or of severely disabled survival. The GCS recognizes gradations of vegetative state and disability, but translating the gradations for rating individual impairment on ordinal scales into a method of assessing percentage impairments cannot be done reliably, as explained in the AMA Guides, Fifth Edition. The AMA Guides also notes that mental and behavioral impairment in Class 4 (marked impairment) or 5 (extreme impairment) indicates “catastrophic impairment” by significantly impeding useful functioning (Class 4) or significantly impeding useful functioning and implying complete dependency on another person for care (Class 5). Translating the AMA Guides guidelines into ordinal scales cannot be done reliably.

Effect of Yoga As Add On Therapy in Migraine (CONTAIN): A Prospective, Randomised, Open Label, Superiority Trial, with Blinded Outcome Assessment

2019 ◽  
Author(s):  
Anand Kumar ◽  
Rohit Bhatia ◽  
Gautam Sharma ◽  
Dhanlika Dhanlika ◽  
Vishnubhatla Sreenivas ◽  
...  
Keyword(s):  
Outcome Assessment ◽  
Open Label ◽  
Superiority Trial

Integrating Bioinformatics Strategies in Cancer Immunotherapy: Current and Future Perspectives

2020 ◽  
Vol 23 (8) ◽  
pp. 687-698 ◽  
Author(s):  
Houda N. Washah ◽  
Elliasu Y. Salifu ◽  
Opeyemi Soremekun ◽  
Ahmed A. Elrashedy ◽  
Geraldene Munsamy ◽  
...  
Keyword(s):  
Cancer Immunotherapy ◽  
Therapeutic Potential ◽  
Cell Cancer ◽  
Full Potential ◽  
Future Perspectives ◽  
The Past ◽  
Bioinformatics Tools ◽  
Treatment Paradigm ◽  
Immunotherapy Of Cancer ◽  
Significant Attention

For the past few decades, the mechanisms of immune responses to cancer have been exploited extensively and significant attention has been given into utilizing the therapeutic potential of the immune system. Cancer immunotherapy has been established as a promising innovative treatment for many forms of cancer. Immunotherapy has gained its prominence through various strategies, including cancer vaccines, monoclonal antibodies (mAbs), adoptive T cell cancer therapy, and immune checkpoint therapy. However, the full potential of cancer immunotherapy is yet to be attained. Recent studies have identified the use of bioinformatics tools as a viable option to help transform the treatment paradigm of several tumors by providing a therapeutically efficient method of cataloging, predicting and selecting immunotherapeutic targets, which are known bottlenecks in the application of immunotherapy. Herein, we gave an insightful overview of the types of immunotherapy techniques used currently, their mechanisms of action, and discussed some bioinformatics tools and databases applied in the immunotherapy of cancer. This review also provides some future perspectives in the use of bioinformatics tools for immunotherapy.

scholarly journals Rare Variants Imputation in Admixed Populations: Comparison Across Reference Panels and Bioinformatics Tools

2019 ◽  
Vol 10 ◽  
Author(s):  
Sanjeev Sariya ◽  
Joseph H. Lee ◽  
Richard Mayeux ◽  
Badri N. Vardarajan ◽  
Dolly Reyes-Dumeyer ◽  
...  
Keyword(s):  
Rare Variants ◽  
Bioinformatics Tools

scholarly journals A Guide to the Language of Clinical Outcome Assessment

2020 ◽  
pp. 219256822097897
Author(s):  
Joseph R. Dettori ◽  
Daniel C. Norvell ◽  
Jens R. Chapman
Keyword(s):  
Clinical Outcome ◽  
Outcome Assessment

scholarly journals Whole-Genome Sequencing for Investigating a Health Care-Associated Outbreak of Carbapenem-Resistant Acinetobacter baumannii

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 201
Author(s):  
Sang Mee Hwang ◽  
Hee Won Cho ◽  
Tae Yeul Kim ◽  
Jeong Su Park ◽  
Jongtak Jung ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Acinetobacter Baumannii ◽  
Genome Sequencing ◽  
Snp Analysis ◽  
Whole Genome ◽  
Phylogenetic Tree Analysis ◽  
Web Based ◽  
Hospital Outbreak ◽  
Carbapenem Resistant ◽  
Bioinformatics Tools

Carbapenem-resistant Acinetobacter baumannii (CRAB) outbreaks in hospital settings challenge the treatment of patients and infection control. Understanding the relatedness of clinical isolates is important in distinguishing outbreak isolates from sporadic cases. This study investigated 11 CRAB isolates from a hospital outbreak by whole-genome sequencing (WGS), utilizing various bioinformatics tools for outbreak analysis. The results of multilocus sequence typing (MLST), single nucleotide polymorphism (SNP) analysis, and phylogenetic tree analysis by WGS through web-based tools were compared, and repetitive element polymerase chain reaction (rep-PCR) typing was performed. Through the WGS of 11 A. baumannii isolates, three clonal lineages were identified from the outbreak. The coexistence of blaOXA-23, blaOXA-66, blaADC-25, and armA with additional aminoglycoside-inactivating enzymes, predicted to confer multidrug resistance, was identified in all isolates. The MLST Oxford scheme identified three types (ST191, ST369, and ST451), and, through whole-genome MLST and whole-genome SNP analyses, different clones were found to exist within the MLST types. wgSNP showed the highest discriminatory power with the lowest similarities among the isolates. Using the various bioinformatics tools for WGS, CRAB outbreak analysis was applicable and identified three discrete clusters differentiating the separate epidemiologic relationships among the isolates.

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