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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

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 Lactobacillus fermentum Te007, Pediococcus pentosaceus Te010, L. pentosus 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.

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)0.001
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.040
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 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

Citations13
Published2012
Admission routes1
Has abstractyes

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