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Record W2087713400 · doi:10.1139/s04-048

Spectral impact of inactivating light on photoreactivation of <i>Escherichia coli</i>

2005· article· en· W2087713400 on OpenAlexvenueno aff
Kumiko Oguma, Hiroyuki Katayama, Shinichiro Ohgaki

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2005
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhotolyaseEscherichia coliUltravioletPyrimidine dimerChemistryWavelengthPhotochemistryMaterials scienceOptoelectronicsDNA damageDNA repairDNABiochemistryGene

Abstract

fetched live from OpenAlex

The spectral impact of inactivating light on subsequent photoreactivation of Escherichia coli K12 was investigated. Ultraviolet-induced pyrimidine dimers in the genome of E. coli were determined, while the survival of E. coli was also examined. A medium-pressure UV lamp (MP: 220–580 nm) was equipped with an optical bandpass filter with the peak emission at 230 nm, 254 nm, or 300 nm, in order to characterize the photoreactivation properties. As references, a MP lamp without a filter, a MP lamp with a glass plate (MPG: 300–580 nm), and a low-pressure UV lamp (LP: 254 nm) were also used for inactivation. Medium pressure inactivation at 230 nm, 254 nm, or 300 nm was followed by the photoreactivation of survival ratio, which was comparable to that after LP exposure. Meanwhile, a repressed survival recovery was observed after MP or MPG inactivation. It was therefore indicated that the MP lamp was effective at repressing photoreactivation of E. coli, which was not attributable to the specific MP emission either at 230 nm, 254 nm, or 300 nm. Rather, the simultaneous exposure to broad wavelengths might provide the MP lamp with the repair repressive effect. Key words: endonuclease sensitive site (ESS), Escherichia coli, medium-pressure UV lamp, photoreactivation, spectral impact, ultraviolet (UV) disinfection.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.254
Teacher spread0.248 · 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 teacher head, 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

Citations10
Published2005
Admission routes1
Has abstractyes

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