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Record W2124909247 · doi:10.5539/jfr.v1n1p110

Malaysian Isolates of Lactic Acid Bacteria with Antibacterial Activity against Gram-Positive and Gram-Negative Pathogenic Bacteria

2012· article· en· W2124909247 on OpenAlexvenueno aff
Belal J. Muhialdin, Zaiton Hassan, Mohamed Muftah Ahmed Imdakim, Fredy Kesnawan Shah Abdul Kahar, Mohamed Mustafa Aween

Bibliographic record

VenueJournal of Food Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsnot available
FundersUniversiti Sains Islam Malaysia
KeywordsBacteriaPathogenic bacteriaNalidixic acidMicrobiologyLactic acidLactobacillus fermentumGram-positive bacteriaAntimicrobialBiologyGram-negative bacteriaLactobacillusAntibacterial activityFood scienceFood spoilageAntibioticsFermentationAntibiotic resistanceEscherichia coliLactobacillus plantarumBiochemistry

Abstract

fetched live from OpenAlex

<p>Contamination of foodstuff with foodborne and pathogenic bacteria are global issue and it is serious hazard for the health of the human. Lactic acid bacteria are well known for their health properties and their antimicrobial activity against spoilage and pathogenic bacteria. In this study, three isolates <em>Lactobacillus fermentum </em>Te007,<em> Pediococcus pentosaceus </em>Te010, <em>L. pentosus </em>G004 isolated from Malaysian fermented foods and fruits such as (tempeh, tempoyak, guava and banana) were evaluated for their antibacterial activity and antibiotic resistant against Gram-positive and Gram-negative bacteria by dual agar overlay method. The three isolates inhibited the growth of indicator bacteria and the activity was varied between weak and strong. All the isolates were resistant to the antibiotic nalidixic acid and vancomycin. The tested bacteria can be added to food as antibacterial agents to prevent the growth of harmful microorganisms.</p>

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)0.001
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 score0.464
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.285
Teacher spread0.244 · 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

Citations13
Published2012
Admission routes1
Has abstractyes

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