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Record W2056223468 · doi:10.1002/cben.201400026

Current Progresses in Phytase Research: Three‐Dimensional Structure and Protein Engineering

2015· article· en· W2056223468 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemBioEng Reviews · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsUniversity of Lethbridge
FundersNational Key Research and Development Program of ChinaChinese Academy of Sciences
KeywordsPhytaseThermostabilityMonogastricProtein engineeringEnzymeChemistryBiochemistryBiotechnologyFood scienceBiologyNutrientPlant nutritionOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Phytase is one of the most important feed additive enzymes for monogastric animal, because it hydrolyzes the indigestible phytate in the cereal‐based feedstock to release phosphate as an essential nutrient. To understand its molecular machinery, the three‐dimensional structures of various types of phytases and complexes have been studied extensively. For commercial applications, important properties such as higher catalytic efficiency and higher thermostability are desired. Since a phytase with both beneficial characteristics is hardly found in nature, various protein engineering strategies are popular in modifying the existing enzymes with enhanced performance. In this review, the up‐to‐date status of phytase structural and engineering studies is summarized. In addition, structural perspectives of some engineered phytases with improved properties are also provided. These results broaden the understanding of phytases and will be important for phytase applications in the future.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.178
GPT teacher head0.342
Teacher spread0.164 · 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