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Record W2303015818 · doi:10.3389/fmicb.2016.00257

Formaldehyde Stress Responses in Bacterial Pathogens

2016· review· en· W2303015818 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Microbiology · 2016
Typereview
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNational Health and Medical Research CouncilAustralian Research CouncilMedical Research Council
KeywordsFormaldehydeMicrobiologyBiologyBacteriaChemistryGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Formaldehyde is the simplest of all aldehydes and is highly cytotoxic. Its use and associated dangers from environmental exposure have been well documented. Detoxification systems for formaldehyde are found throughout the biological world and they are especially important in methylotrophic bacteria, which generate this compound as part of their metabolism of methanol. Formaldehyde metabolizing systems can be divided into those dependent upon pterin cofactors, sugar phosphates and those dependent upon glutathione. The more prevalent thiol-dependent formaldehyde detoxification system is found in many bacterial pathogens, almost all of which do not metabolize methane or methanol. This review describes the endogenous and exogenous sources of formaldehyde, its toxic effects and mechanisms of detoxification. The methods of formaldehyde sensing are also described with a focus on the formaldehyde responsive transcription factors HxlR, FrmR, and NmlR. Finally, the physiological relevance of detoxification systems for formaldehyde in bacterial pathogens is 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.249
Teacher spread0.236 · 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