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Spider dragline silk proteins in transgenic tobacco leaves: accumulation and field production

2004· article· en· W1917760679 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

VenuePlant Biotechnology Journal · 2004
Typearticle
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyTransgeneSILKGenetically modified cropsBiotechnologyKDELRecombinant DNAGeneGenetics

Abstract

fetched live from OpenAlex

Spider dragline silk is a unique biomaterial and represents nature's strongest known fibre. As it is almost as strong as many commercial synthetic fibres, it is suitable for use in many industrial and medical applications. The prerequisite for such a widespread use is the cost-effective production in sufficient quantities for commercial fibre manufacturing. Agricultural biotechnology and the production of recombinant dragline silk proteins in transgenic plants offer the potential for low-cost, large-scale production. The purpose of this work was to examine the feasibility of producing the two protein components of dragline silk (MaSp1 and MaSp2) from Nephila clavipes in transgenic tobacco. Two different promoters, the enhanced CaMV 35S promoter (Kay et al., 1987) and a new tobacco cryptic constitutive promoter, tCUP (Foster et al., 1999) were used, in conjunction with a plant secretory signal (PR1b), a translational enhancer (alfalfa mosaic virus, AMV) and an endoplasmic reticulum (ER) retention signal (KDEL), to express the MaSp1 and MaSp2 genes in the leaves of transgenic plants. Both genes expressed successfully and recombinant protein accumulated in transgenic plants grown in both greenhouse and field trials.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.399

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 head0.025
GPT teacher head0.268
Teacher spread0.243 · 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