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Record W7135648518

The evaluation of in vitro activity of potentially antifungal compounds by microdilution broth method. VIII.

2007· dissertation· cs· W7135648518 on OpenAlexaboutno aff
Lenka Kvítková

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2007
Typedissertation
Languagecs
FieldBiochemistry, Genetics and Molecular Biology
TopicPhenothiazines and Benzothiazines Synthesis and Activities
Canadian institutionsnot available
Fundersnot available
KeywordsBroth microdilutionAntifungalIn vitroIncubationTrichophytonMinimum inhibitory concentration
DOInot available

Abstract

fetched live from OpenAlex

Kvítková L.: Evaluation of in vitro activity of potentially antifungal compounds by microdilution broth method - VIII. Over 250 new synthetized compounds divided into 16 chemical groups were tested by microdilution broth method for the establisment of in vitro antifungal activity. This method is based on the standard M27-A (Clinical Laboratory Standard Institute). RPMI 1640 medium buffered to pH 7.0 with MOPS was used and standardized inoculum was prepared from fresh fungal isolates grown on Sabouraud agar. All compounds tested were dissolved and diluted in DMSO. The MICs were determinated visually after 24 or 48 hours of incubation at 35C. The compounds were tested against eight fungal strains. The structure-activity relationships were studied and compared with the calculated log P values. Hydrophobicity of compounds (log P) was computed using the program ACD/LogP (Advanced Chemistry Development Inc., Ontario, Canada). The most active compounds were the derivatives of (E)-1-pyrazine-2- ylethane-1-one-thiosemicarbazone; the majority of the compounds showed moderate or high efficacy against all fungal strains tested. There were several compounds of the groups tested with a considerable antifungal effect, as well. The most susceptible fungal strain was Trichophyton mentagrophytes, on the contrary,...

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.011
GPT teacher head0.295
Teacher spread0.284 · 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.

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
Published2007
Admission routes1
Has abstractyes

Explore more

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