Identification and quantification of proteins in Malus domestica affected by bitter pit
Bibliographic record
Abstract
Bitter pit is a physiological disorder that occurs in apple, pear, and quince and has been associated with calcium uptake or lack thereof. Although bitter pit has been studied for over a century, there is still not enough knowledge about bitter pit and why there are no completely effective preventive treatments to reduce fruit loss. In a previous group publication (Val et al. 2006), it was conjectured after SDS-PAGE that an unknown 18 kDa protein might contribute to bitter pito The objective of the present study was to identify this 18 kDa protein and get more extensive data on the proteomic changes associated to bitter pit using the latest mass spectrometry-based proteomics. Healthy and bitter pit fruit samples (Malus domesica 'Reinette gris du Canada' and Malus domestica 'Golden Smoothee') were collected near Zaragoza (Aragón, Spain). Following phenol extraction, ten µg protein were allowed to run on SDS-PAGE, trypsin digested, and digestion products were analyzed on a Q-Exactive mass spectrometer (Thermo Scientific). Proteins were identified with X!Tandem pipeline software (http://pappso.inra.fr/) and relative quantification was performed by spectral counting. More than two hundred proteins were identified in the range of 12-24 kDa. We focused on 35 proteins that varied significantly between the two conditions (bitter pit vs. healthy) being over/under expressed. There were 26 and 22 bitter pit proteins ('Reinette gris du Canada' and 'Smoothee Golden Delicious,' respectively) detected with at least 50% greater abundance when compared to their respective healthy counterparts. Among these proteins, 14 found in both cultivars, were identified as Pathogenesis-related protein Bet v 1, a major allergen found in trees within the order Fagales. In both apple cultivars, 2 proteins were identified as thaumatin-like protein (TLP), a group of proteins responsible for several fruit allergies. Glutathione S-transferase, linked to protein binding and heat shock transcriptional factors (Hsfs) in Malus, was abundantly detected in bitter pit samples for both cultivars. Several proteins identified near or at 18-kDa, are related to Malus domestica' response to stress, desiccation, and increased protein binding. Considerable differences were found in allergen concentrations between bitter pit and healthy samples, suggesting an increased allergen risk for consumers who ingest bitter pit affected fruit.
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How this classification was reachedexpand
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 | 0.002 | 0.007 |
| 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 teacher head, 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".