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Record W2906673440 · doi:10.1039/c8tx00267c

Bacterial toxicity of biomimetic green zinc oxide nanoantibiotic: insights into ZnONP uptake and nanocolloid–bacteria interface

2018· article· en· W2906673440 on OpenAlexfundno aff
Bilal Ahmed, Bushra Solanki, Almas Zaidi, Javed Musarrat

Bibliographic record

VenueToxicology Research · 2018
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsnot available
FundersInstitute of Population and Public HealthCouncil of Science and Technology, U.P.King Saud University
KeywordsZincBacteriaToxicityNanotechnologyMaterials scienceChemistryBiotechnologyBiologyMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

ions in a nutrient medium increased as a result of interaction with the bacterial surface and metabolites. Substantial surface binding of ZnONPs followed by intracellular uptake disrupted the cell morphology and caused obvious injury to the cell membrane. Interrupted bacterial growth kinetics, loss of cell respiration, enhanced production of intracellular ROS, and the leakage of the cytoplasmic content unequivocally suggested a strong interaction of ZnONPs with the exterior cell surface and intracellular components, eventually leading to cell death and destruction of biofilms. Overall, the results elucidated eco-friendly production of ZnONPs expressing a prominent interfacial correlation with bacteria and hence, prospecting the use of green ZnONPs as effective nanoantibiotics.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.053
GPT teacher head0.358
Teacher spread0.305 · 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 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

Citations144
Published2018
Admission routes1
Has abstractyes

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