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Record W1901983113 · doi:10.5376/ijccr.2013.03.0006

Efficacy of Bioactive Compounds of Sponges to Prevent Biofilm Formation on Medical Implants

2013· article· en· W1901983113 on OpenAlexvenueno aff
K. Chairman, K. Elizabath Mathew, R. Vigila Christy, C. Padmalatha, Ameet Singh

Bibliographic record

VenueInternational Journal of Clinical Case Reports · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsnot available
Fundersnot available
KeywordsBiofilmSpongeMicrobiologyChemistryDentistryMedicineBiologyBacteria

Abstract

fetched live from OpenAlex

Bacterial biofilms are surface-attached communities of microorganisms that are protected by an extracellular matrix of biomolecules. In the biofilm state, bacteria are significantly more resistant to external assault, including attack by antibiotics. In their native environment, bacterial biofilms underpin costly biofouling that wreaks havoc on shipping, utilities, and offshore industry. Within a host environment, they are insensitive to antiseptics and basic host immune responses. It is estimated that up to 80% of all microbial infections are biofilm-based. Biofilm infections of indwelling medical devices are of particular concern, since once the device is colonized, infection is almost impossible to eliminate. Importantly, we discuss several sets of compounds derived from marine sponges that we are developing in our labs to address the persistent biofilm problem. Marine bioactive compound synthesis of natural products and their analogues-including our marine sponge-derived compounds and initial adjuvant activity and toxicological screening of our novel anti-biofilm compounds.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.030
GPT teacher head0.393
Teacher spread0.362 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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