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Record W3007569245 · doi:10.1080/00032719.2020.1731524

Identification of <i>Salmonella</i> Serovars before and after Ultraviolet Light Irradiation by Fourier Transform Infrared (FT-IR) Spectroscopy and Chemometrics

2020· article· en· W3007569245 on OpenAlexfundno aff
Cristina M. Muntean, Nicoleta Elena Dina, Flaviu Tăbăran, Ana Maria Raluca Gherman, Alexandra Fălămaș, Loredana Olar, Liora Colobățiu, Răzvan Ștefan

Bibliographic record

VenueAnalytical Letters · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsnot available
FundersOntario Ministry of Research, Innovation and Science
KeywordsChemistryIrradiationAbsorbanceFourier transform infrared spectroscopyInfraredChemometricsInfrared spectroscopyUltravioletSpectroscopyBacteriaAnalytical Chemistry (journal)ChromatographyOpticsMaterials scienceBiologyOrganic chemistryGeneticsOptoelectronics

Abstract

fetched live from OpenAlex

Vibrational properties and structural behavior upon ultraviolet (UV) irradiation are reported here for DNAs isolated from three serovars of Salmonella bacteria, respectively (S. enteritidis, S. infantis and S. typhimurium) by using Fourier transform infrared spectroscopy (FT-IR). The FT-IR absorbance spectra were recorded for bacterial DNAs, control and UV irradiated samples (30 min, 1 h, 1 h 30 min), respectively, and are presented in the wavenumber ranges from 800 to 1800 cm−1 and from 3000 to 4000 cm−1, respectively. Molecular specific structural information has been found based on DNA marker bands, which were monitored primarily in terms of intensity changes. As a general remark, a serovar’s dependent nonlinear behavior has been detected for some FT-IR band intensities corresponding to Salmonella DNAs, as a function of irradiation time. Particularly, alterations in DNA functional groups and molecular geometry have been observed. Chemometric analysis such as principal component analysis (PCA) and hierarchical clustering analysis (HCA) were successfully applied for the identification of inter- and intra- serovar differences between DNA spectra, before and after UV irradiation. The elucidation of the main spectral features characteristic to pathogenic bacterial DNAs offers further opportunity for bacteria identification and for establishing the mechanisms of infections, leading to the development of innovative diagnosis tools and more effective therapies. Particularly, DNA-damaging agents are most effective in cancer therapy.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.303

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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 designObservational
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

Citations4
Published2020
Admission routes1
Has abstractyes

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