45 ANALYSIS OF DIFFERENTIALLY EXPRESSED PROTEINS IN THE PLACENTA OF SOMATIC CELL CLONED AND ARTIFICIAL INSEMINATION PIG PLACENTA USING PROTEOMICS
Bibliographic record
Abstract
Somatic cell cloning has been hampered by biological and technical problems. A major limitation of cloning procedures is the extreme inefficiency of producing healthy offspring for reasons such as sudden intrauterine unexplained death and infant death syndrome. In this study, we analyzed differentially expressed protein profiles in the placenta of somatic cell cloned (SCNT) and artificial insemination (AI; control) pigs by proteomics. Protein expression pattern of placentas was established in the pH range 4–7, IEF cell system, and 7.5–17.5% gradient 2-dimensional polyacrylamide gel electrophoresis. Image analysis following silver staining used the spot and PDQuest analysis system. Peptide mass fingerprinting with matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry and SWISS-PROT database search were utilized to identify proteins. Around 1000 protein spots were recognized by image analysis on each placenta. In SCNT pig placentas, 37 spots were changed compared with those of AI pig placentas. Among them 11 proteins such as serum albumin precursor and annexin A5 showed an increased protein expression level whereas the expression level of 26 other proteins such as aldose reductase and tropomyosin decreased. Annexin A5 and aldose reductase are implicated in the apoptosis process: the former is an apoptotic marker of oxidative stress; on the other hand, the latter is a critical regulator of TNF-a-induced apoptotic signaling in endothelial cells. Also, tropomyosin is implicated in stabilizing cytoskeleton actin filaments. The expression of these proteins was confirmed by western blot and real-time PCR analysis. These results suggest expression of abnormal placental protein and apoptotic-related protein in SCNT pig placentas affects the regulation of placental growth and development. This work was supported in part by a grant program from RDA(Biogreen21) and Cho-A, Republic of Korea.
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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) | 0.001 | 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".