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Record W2124867258 · doi:10.1186/2008-2231-21-71

Are other fluorescent tags used instead of ethidium bromide safer?

2013· article· en· W2124867258 on OpenAlexaff
Soodabeh Saeidnia, Mohammad Abdollahı

Bibliographic record

VenueDARU Journal of Pharmaceutical Sciences · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsEthidium bromideAgarose gel electrophoresisDNAChemistrySYBR Green IAgaroseComet assayMolecular biologyNucleaseBiologyDNA damageBiochemistryReal-time polymerase chain reactionGene

Abstract

fetched live from OpenAlex

Ethidium bromide (EtBr) is a well-known fluorescent tag usually applied in molecular biological techniques like agarose gel electrophoresis. The mechanism of action for such compounds is known, in which these compounds are able to bind to the kinetoplastid DNA and to alter their conformation to Z-DNA molecules that stop replication of kinetoplastid DNA leading to Trypanosoma death. Although the usual amounts used in laboratories are considered as below the level required to cause toxicity (LD50 in oral administration in rat is 1.5 g/Kg), the mentioned concentrations are high enough to involve in replication of mitochondrial DNA in some human cell lines. Regarding the points that EtBr is very stable in the environment and if degraded especially by use of bleaches that result in formation of mutagenic compounds, there is a big concern about its use. Although application of EtBr is going to be restricted and replaced with other tags such as SYBR® products, the safety of the new substituted compounds are still in doubt and except a few data, there is no essential evidence available to confirm that they are safer than EtBr. Further investigations are recommended to compare their relative biosafety hazards.

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.006

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 head0.056
GPT teacher head0.362
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations46
Published2013
Admission routes1
Has abstractyes

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