Phorbol 12-myristate 13-acetate (PMA) Alters Galectin Gene Expression in Cows
Bibliographic record
Abstract
Galectins (GAL) are β-galactoside binding proteins. The objective of this study was to assess the effect of PMA on the regulation of galectin gene expression in bovine blood and neutrophils. Blood was collected from 3 clinically healthy Holstein cows. Neutrophils were isolated by differential centrifugation. Blood and neutrophils were treated with 10ng/ml of PMA or maintained in phosphate-buffered saline for 30 minutes at 370 C. Pooled total RNA were transcribed to cDNA for real-time PCR. Specific primers for bovine LGALS -1, -2, -3, -4, -7, -8, -9, -11, -12, and their binding proteins (bp) LGALS3bp, T cell immunoglobulin and mucin domain 3 (TIM-3) were used. Housekeeping genes RPLP0 and UCHL5 served as internal controls. Fold changes were calculated using the Livak method. Total protein concentration was assessed using the Bicinchoninic acid assay. Secretion of GAL -1, -2, -3, -4, -8, -9 was assessed using bovine GAL specific ELISA. All tested LGALS were detected. Activation with PMA differentially modulated expression and secretion of GAL in blood and neutrophils. Expression levels of LGALS -1 and LGALS -3 was not affected. Expression of LGALS -7, -8, -9, -11, -12, and TIM-3 was differentially modulated. The secretion of GAL -3 was significantly increased in response to PMA. The most pronounced effect of PMA was observed on LGALS-9, TIM-3 expression, and the secretion of GAL -3. Thus, GAL may serve as biomarkers of cell activation with functional consequences and warrant further study.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".