Galectin-14 expression in ovarian cancer
Bibliographic record
Abstract
Abstract Galectins (gal) are multifunctional proteins whose expression changes under different physiological or pathological conditions, including cancer. However, so far, most studies have focused on gal-1 and gal-3, and to a lesser extent to gal-7 and gal-9. We still know very little about other galectins, especially the recently discovered ones, such as gal-14, a prototype galectin highly expressed at the maternal-fetal interface. Here, using in silico and in vitro approaches, we report a correlation between lgals14 expression and ovarian cancer. We found that high expression of gal-14 mRNA in ovarian cancer cells is associated with a shorter survival. Consistent with this observation, we also found that lgals14 is preferentially expressed in high grade serous adenocarcinoma (HGSA) ovarian cancer. Our in vitro data with ovarian cancer cell lines confirmed that lgals14 is readily expressed in HGSA. Interestingly, de novo expression of gal-14 in HEK-293 cells increased apoptosis, both at the basal level and following exposure to low doses of etoposide. Thus, although the study of this galectin is still in its infancy, we were able to provide novel insights into the expression patterns of this galectin and its involvement in cancer.
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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 | 0.001 | 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".