Proteomics analysis of <i>Trichoplusia ni</i> midgut epithelial cell brush border membrane vesicles
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".