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Record W2099494724 · doi:10.1139/w2012-025

Chromosomal bacterial type II toxin–antitoxin systems

2012· review· en· W2099494724 on OpenAlexaffvenue
Mohammad Adnan Syed, Céline M. Lévesque

Bibliographic record

VenueCanadian Journal of Microbiology · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAntitoxinBiologyToxinArchaeaGeneBacteriaRNAGeneticsMicrobiology

Abstract

fetched live from OpenAlex

Most prokaryotic chromosomes contain a number of toxin-antitoxin (TA) modules consisting of a pair of genes that encode 2 components, a stable toxin and its cognate labile antitoxin. TA systems are also known as addiction modules, since the cells become "addicted" to the short-lived antitoxin product (the unstable antitoxin is degraded faster than the more stable toxin) because its de novo synthesis is essential for their survival. While toxins are always proteins, antitoxins are either RNAs (type I, type III) or proteins (type II). Type II TA systems are widely distributed throughout the chromosomes of almost all free-living bacteria and archaea. The vast majority of type II toxins are mRNA-specific endonucleases arresting cell growth through the mechanism of RNA cleavage, thus preventing the translation process. The physiological role of chromosomal type II TA systems still remains the subject of debate. This review describes the currently known type II toxins and their characteristics. The different hypotheses that have been proposed to explain their role in bacterial physiology are also discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations26
Published2012
Admission routes2
Has abstractyes

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