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Record W7006194709

Structural characterization of FmtA: a new esterase from Staphylococcus aureus

2024· dissertation· es· W7006194709 on OpenAlexaboutno aff

Bibliographic record

VenueRiuNet (Politechnical University of Valencia) · 2024
Typedissertation
Languagees
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Work (physics)Structure functionMeta heuristic
DOInot available

Abstract

fetched live from OpenAlex

[ES] La FmtA es una proteína reconocedora de penicilina con una función esterasa que consiste en hidrolizar el enlace éster que une la D-alanina a la cadena principal de los ácidos teicoicos. Se trata de una proteína de interés porque actúa sobre los ácidos teicoicos y desempeña un papel clave en la síntesis de la pared celular bacteriana, lo que la sitúa en el punto de mira como posible diana terapéutica. El presente trabajo consiste en la expresión, purificación y cristalización de esta proteína con el fin de obtener -mediante cristalografía de rayos X- datos estructurales que permitan la elucidación estructural de la proteína. A partir de los datos de difracción obtenidos, se llevan a cabo ciclos de modelado y refinamiento del modelo estructural de FmtA para analizar la estructura de la proteína e identificar sus aspectos más relevantes. Se trata de un trabajo en colaboración con la Prof. Dasantila Golemi-Kotra, del Departamento de Biología de la Universidad York de Toronto (Canadá). Anteriormente la Prof. Golemi-Kotra resolvió una primera estructura de FmtA libre de ligandos a baja resolución, pero no pudo continuar la caracterización estructural porque los cristales no eran reproducibles. El trabajo actual pretende reproducir los cristales de FmtA para obtener datos de difracción a mayor resolución que nos permitan una comprensión más detallada de esta proteína diana.

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 score0.003
Threshold uncertainty score0.006

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)0.0010.000

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 head0.023
GPT teacher head0.223
Teacher spread0.200 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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