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Record W4389799374 · doi:10.1101/pdb.prot108283

Membrane Protein Fractionation and Analysis through Western Blot in<i>Aedes aegypti</i>Malpighian Tubules

2023· article· en· W4389799374 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

VenueCold Spring Harbor Protocols · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsYork University
Fundersnot available
KeywordsWestern blotFractionationMembrane proteinCell fractionationBlotBiologyCytosolBiochemistryProtein purificationBacterial outer membraneChemistryMembraneChromatography

Abstract

fetched live from OpenAlex

Western blot analysis is a well-known and dependable technique used to quantify protein abundance in a wide variety of samples. A major consideration for running a successful western blot is ensuring that the protein to be analyzed is purified appropriately. For work with membrane-bound proteins, traditional methods of protein processing such as the use of high-frequency sonication and ultracentrifugation to separate proteins from the membrane are being replaced with less time-consuming approaches. The use of a membrane fractionation kit, which involves the separation of membrane proteins from soluble (cytosolic) proteins, is effective in allowing for the quantification and analysis of membrane-bound proteins. In this protocol, we describe use of the membrane fractionation kit to isolate membrane-bound proteins, followed by western blot analysis, to observe protein abundance. The protocol involves methods that require organ (or tissue) collection, followed by protein processing, and a 2-d western blot procedure.

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 score0.210
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.290
Teacher spread0.273 · 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