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Record W2794093518 · doi:10.1101/250902

Generation of a novel growth-enhanced and reduced environmental impact transgenic pig strain

2018· preprint· en· W2794093518 on OpenAlexaff
Xianwei Zhang, Zicong Li, Huaqiang Yang, Dewu Liu, Gengyuan Cai, Guoling Li, Jianxin Mo, Dehua Wang, Cuili Zhong, Haoqiang Wang, Yue Sun, Junsong Shi, Enqin Zheng, Fanming Meng, Mao Zhang, Xiaoyan He, Rong Zhou, Jian Zhang, Miaorong Huang, Ran Zhang, Ning Li, Fanming Zhe, Jinzeng Yang, Zhenfang Wu

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsUniversity of Guelph
FundersSouth China Agricultural UniversityChina Agricultural University
KeywordsPhytaseTransgeneXylanaseDigestion (alchemy)StarchNutrientBiologyPhosphorusNitrogenGenetically modified cropsFeed conversion ratioFecesStrain (injury)Food scienceEnzymeAgronomyAnimal scienceBiotechnologyChemistryBiochemistryMicrobiologyBody weightGeneEndocrinologyChromatography

Abstract

fetched live from OpenAlex

ABSTRACT In pig production, insufficient feed digestion causes excessive nutrients such as phosphorus and nitrogen, which are then released to the environment. To address the issue of environmental emissions, we have established transgenic pigs harboring a single-copy quad-cistronic transgene and simultaneously expressing three microbial enzymes, β-glucanase, xylanase, and phytase in the salivary glands. All the transgenic enzymes were successfully expressed, and the digestion of non-starch polysaccharides (NSPs) and phytate in the feedstuff was enhanced. Fecal nitrogen and phosphate outputs were reduced by 23%–46%, and growth rate improved by 23.4% (gilts) and 24.4% (boars) when the pigs were fed on a corn and soybean-based diet and high-NSP diet. The transgenic pigs showed a 11.5%– 14.5% improvement in feed conversion rate compared to the age-matched wild-type littermates. These findings indicate that transgenic pigs are promising resources for improving feed efficiency and reducing nutrient emissions to the environment.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.066
Threshold uncertainty score1.000

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 head0.020
GPT teacher head0.236
Teacher spread0.216 · 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
Published2018
Admission routes1
Has abstractyes

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