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Record W2968145325 · doi:10.1111/iej.13137

Animal testing: a re‐evaluation of what it means to Endodontology

2019· editorial· en· W2968145325 on OpenAlexaffabout
Venkateshbabu Nagendrababu, Peter E. Murray, Anil Kishen, M. H. Nekoofar, José Antônio Poli de Figueiredo, P. M. H. Dummer

Bibliographic record

VenueInternational Endodontic Journal · 2019
Typeeditorial
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAnimal testingAnimal welfareEuropean unionMedicineEnvironmental healthBusinessBiologyInternational trade

Abstract

fetched live from OpenAlex

Animal testing has a long history in the biological evaluation of medical devices used in Dentistry (ISO 7405). Indeed, tests on animals have been used to develop new interventions, materials, devices and drugs as they tend to provide information on their biological mechanisms of action, as well as their efficacy and side-effects before human applications (Singh et al. 2016). As an example, animal studies supported the basis for the understanding of orofacial development (Sharpe 1995). However, animal tests are not essential and may be prohibited by international and local laws, for example, the European Union animal testing ban for cosmetics (EU Regulation No 1223/2009) and the California Cruelty-Free Cosmetics Act (SB-1249). The animal testing bans indicate a public policy shift away from animal testing, to placing more reliance on the results from lab-on chip, organ-on-chip, human cell-based studies and clinical trials, to reduce the number of animals that are sacrificed and protect patient or consumer health and safety (Kimura et al. 2018). It has been estimated that 115 million animals are used for research testing worldwide each year, mostly in the United States, Japan, China, Australia, France, Canada, the United Kingdom, Germany and Brazil (Taylor et al. 2008). Animal testing is not in decline, and in many parts of the world it is on the increase or remains at the same level as in the 1980s or 1990s (Taylor et al. 2008). The most common animals used in testing are mice, rats, birds, sheep, guinea-pigs, monkeys, dogs, cats, pigs, goats and cows. Up to 97% of dog and cat owners regard their animals as a member of their family (Risely-Curtiss et al. 2006). Moving forward, it cannot be acceptable to publish tests done on dogs and cats, because they are most often viewed as family members, not laboratory animals. Animal testing can be made more morally and ethically acceptable, by trusting animal welfare to the extensive regulations governing animal tests. However, more protections to prevent animal pain and suffering are mandatory, in addition to the safety net of animal welfare regulations. Today, there can be no ethical justification to publish articles where there was a lack of pain monitoring, and where the pain relief measures appeared to be inadequate, to prevent avoidable animal suffering. Poor quality animal studies tend to produce clinically unreliable results (Pound & Bracken 2014, Singh et al. 2016), which can defeat the purpose of animal testing, rendering it useless. Steps to improve the quality of animal research, the ARRIVE (Animal Research: Reporting In Vivo Experiments) guidelines (Kilkenny et al. 2010) and the SYRCLE (Systematic Review Centre for Laboratory animal Experimentation) risk of bias tool (Hooijmans et al. 2014) were developed to guide researchers. However, animal studies in Endodontology often need exclusive information related to the specialty. Hence, we are proposing new guidelines named: ‘Preferred Reporting Items for Animal Studies in Endodontology (PRIASE)’, which can improve the quality of animal welfare and results, thereby improving the effectiveness, reproducibility and clinical translation of animal studies in Endodontology. With so much cognitive dissonance (inconsistent thoughts, beliefs and attitudes) towards animal testing, by wanting to keep benefiting from its safeguards, and to stop it at the same time, arriving at a consensus policy that satisfies all stakeholders may be impossible until we look at ourselves, our traditional values and our strengths. The field of Endodontology has attained an elevated social and professional purpose, due to our unique problem-solving skills to relieve and prevent pain, act with integrity and compassion, save teeth to improve a person's quality of life, give people the ability to eat and communicate, preserve a person's appearance and emotional identity. Now is the time to apply some of our unique skills and strengths to animal testing by developing and implementing the PRIASE guidelines.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.147
metaresearch head score (Gemma)0.178
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score0.775

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1470.178
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0080.005
Science and technology studies0.0030.039
Scholarly communication0.0130.016
Open science0.0070.008
Research integrity0.0120.021
Insufficient payload (model declined to judge)0.0100.007

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 head0.246
GPT teacher head0.456
Teacher spread0.210 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainMethods
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2019
Admission routes2
Has abstractyes

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