Galectin-7 Impairs Placentation and Causes Preeclampsia Features in Mice
Bibliographic record
Abstract
Preeclampsia is a serious pregnancy-induced disorder unique to humans. The etiology of preeclampsia is poorly understood; however, poor placental formation is thought causal. Galectin-7 is produced by trophoblast and is elevated in first-trimester serum of women who subsequently develop preeclampsia. We hypothesized that elevated placental galectin-7 may be causative of preeclampsia. Here, we demonstrated increased galectin-7 production in chorionic villous samples from women who subsequently develop preterm preeclampsia compared with uncomplicated pregnancies. In vitro, galectin-7 impaired human first-trimester trophoblast outgrowth, increased placental production of the antiangiogenic sFlt-1 splice variant, sFlt-1-e15a , and reduced placental production and secretion of ADAM12 (a disintegrin and metalloproteinase12) and angiotensinogen. In vivo, galectin-7 administration (E8–E12) to pregnant mice caused elevated systolic blood pressure, albuminuria, impaired placentation (reduced labyrinth vascular branching, impaired decidual spiral artery remodeling, and a proinflammatory placental state demonstrated by elevated IL1β, IL6 and reduced IL10), and dysregulated expression of renin-angiotensin system components in the placenta, decidua, and kidney, including angiotensinogen, prorenin, and the angiotensin II type 1 receptor. Collectively, this study demonstrates that elevated galectin-7 during placental formation contributes to abnormal placentation and suggests that it leads to the development of preeclampsia via altering placental production of sFlt-1 and renin-angiotensin system components. Targeting galectin-7 may be a new treatment option for preeclampsia.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".