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Record W2097933864 · doi:10.5539/ijb.v2n2p213

Arsenic toxicity in pathogenic Staphylococcus epidermidis and Klebsiella pneumoniae

2010· article· en· W2097933864 on OpenAlexvenueno aff
Neeta N. Surve, Uttamkumar S. Bagde

Bibliographic record

VenueInternational Journal of Biology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsStaphylococcus epidermidisArsenicKlebsiella pneumoniaeMicrobiologyToxicityArsenic toxicityBiologyBiochemistryChemistryBacterial growthCytoplasmBacteriaStaphylococcus aureusEscherichia coli

Abstract

fetched live from OpenAlex

The sensitivity of pure cultures of Staphylococcus epidermidis and Klebsiella pneumoniae towards arsenic was studied with particular reference to biochemical changes induced by the heavy metal in these organisms. Arsenic strongly inhibited the growth and viability of both the organisms. Addition of arsenic prolonged the lag phase and this was found to be the concentration dependent phenomenon. The Minimum inhibitory concentration (MIC) determined was 200 ppm and 20 ppm in S. epidermidis and K. pneumoniae respectively that inhibited growth, synthesis of protein, DNA, RNA completely and activity of dehydrogenases of the TCA cycle. In S. epidermidis and K. pneumoniae, cell wall, membrane and cytoplasm 24.5%, 32.5%, 43% and 20%, 35%, 45% arsenic respectively got incorporated. As the activity of dehydrogenases was inhibited by arsenic, cells were incapable of oxidizing substrate. It resulted in limited supply of energy rich compounds such as ATP that affected the synthesis of macromolecules. Ultimately multiplication and growth of the organism got ceased.

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 score0.739
Threshold uncertainty score0.760

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)0.0010.000

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 head0.257
Teacher spread0.250 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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