Proteomics analysis of <i>Trichoplusia ni</i> midgut epithelial cell brush border membrane vesicles
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.
Bibliographic record
Abstract
The insect midgut epithelium is composed of columnar, goblet, and regenerative cells. Columnar epithelial cells are the most abundant and have membrane protrusions that form the brush border membrane (BBM) on their apical side. These increase surface area available for the transport of nutrients, but also provide opportunities for interaction with xenobiotics such as pathogens, toxins and host plant allelochemicals. Recent improvements in proteomic and bioinformatics tools provided an opportunity to determine the proteome of the T. ni BBM in unprecedented detail. This study reports the identification of proteins from BBM vesicles (BBMVs) using single dimension polyacrylamide gel electrophoresis coupled with multi-dimensional protein identification technology. More than 3000 proteins were associated with the BBMV, of which 697 were predicted to possess either a signal peptide, at least one transmembrane domain or a GPI-anchor signal. Of these, bioinformatics analysis and manual curation predicted that 185 may be associated with the BBMV or epithelial cell plasma membrane. These are discussed with respect to their predicted functions, namely digestion, nutrient uptake, cell signaling, development, cell-cell interactions, and other functions. We believe this to be the most detailed proteomic analysis of the lepidopteran midgut epithelium membrane to date, which will provide information to better understand the biochemical, physiological and pathological processes taking place in the larval midgut.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it