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Record W4389834824 · doi:10.7860/jcdr/2023/68275.18809

A Scoping Review on the Ethical Issues in the Use of CRISPR-Cas9 in the Creation of Human Disease Models

2023· review· en· W4389834824 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsCRISPRCas9DiseaseComputer sciencePaceGenome editingEngineering ethicsData scienceMedicineBiologyGeneticsEngineeringGenePathologyGeography

Abstract

fetched live from OpenAlex

Introduction: The remarkable advances in molecular science and technology have dramatically changed the landscape of Deoxyribonucleic Acid (DNA). With the rapid pace of new gene editing technologies like Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9 (CRISPR-Cas9), human disease models can be created to reduce the burden of morbidity and mortality caused by genetic defects and congenital malformations. However, despite its potential to advance human health and well-being, the use of CRISPR-Cas9 technology raises numerous ethical concerns, including the lack of a well-defined regulatory framework. Aim: To outline the ethical concerns that arise in the creation of human disease models using CRISPR-Cas9 technology and to design a conceptual framework to identify the ethical challenges and address these concerns. Materials and Methods: The data on ethical issues in the use of CRISPR-Cas9 in the creation of human disease models were obtained by reviewing 530 articles retrieved from scientific databases such as Google Scholar, PubMed, Scopus, and Excerpte Medica dataBASE (EMBASE) from the year 2015. Based on the eligibility criteria, 24 publications from 56 full-text articles that were screened were included in this study. The selection process was conducted in three phases-screening of the title, abstract, and full text. The articles selected after full-text screening were analysed, and the data was scrutinised independently. Tables, charts, figures, and graphs were used to organise and illustrate the obtained data. The entire paper was drafted using the Preferred Repoting Items for Systematic Reviews and Meta-analyses (PRISMA) extension for scoping review reporting criteria. Results: The present study included 24 articles for review after the screening process. The articles emphasised the bioethical issues related to CRISPR-Cas9 technology and gene editing while also shedding light on the current level of research in the field. The studies included different countries, with the maximum number of papers from the United States of America (USA), followed by the United Kingdom (UK), China, Turkey, Spain, Canada, Pakistan, Australia, Italy, France, Korea, and Sri Lanka. These articles were published between 2015 and 2021. The disease for which models were created was not mentioned in the majority of articles, while a few investigated the application of CRISPR-Cas9 in genetic disorders, cardiovascular diseases, neurodegenerative diseases, and eye disorders. The major ethical concerns identified included safety, efficacy, unintended consequences, harm to the environment, off-target effects, obtaining informed consent, and the risk of misuse. Conclusion: The use of CRISPR-Cas9 technology in creating human disease models has raised many ethical concerns. One of the primary ethical issues is the potential for unintended consequences, which could have serious long-term effects on individuals and their offspring. To address these ethical issues, it is important to develop ethical guidelines and best practices, as well as to support ongoing research to investigate the longterm effects of gene modifications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.040
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.602
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.557
GPT teacher head0.644
Teacher spread0.087 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it