Diabetes Mellitus During Pregnancy Interferes with the Biological Characteristics of Wharton's Jelly Mesenchymal Stem Cells
Bibliographic record
Abstract
Recent research indicates that the origin of obesity and related metabolic disorders is not only caused by genetic and risk factors in adult life (unbalanced diet, insufficient physical activity) but also may be influenced by the perinatal environment.In addition, studies in animal models suggest that the mesenchymal stem cell commitment into pre-adipocytes can already occur during fetal development and perinatal life.Since the number of pre-adipocytes and mature adipocytes is lower in normal subjects than in obese subjects, changes in the prenatal maturational process may play a role in the pathogenesis of obesity and metabolic-associated diseases.Hyperglycemia during pregnancy is related to an increased risk of obesity, early onset of metabolic syndrome and type 2 diabetes in the offspring.For this reason it would be useful to investigate how the perinatal environment may affect fetal mesenchymal stem cells, especially in deregulated gestational diabetes, where the fetal environment is modified in terms of hormone levels and nutrition.Therefore, we have compared Wharton's jelly mesenchymal stem cells (WJ-MSC) obtained from umbilical cord of both healthy and diabetic mothers, in order to better understand the mechanisms involved in metabolic diseases in offspring of diabetic mothers.Results indicate that WJ-MSC from diabetic mothers display, in contrast to cells from healthy mothers, a higher ability to differentiate towards the adipogenic lineage.This suggests that the diabetic uterine environment may be responsible for a "pre-commitment" that could give rise in the post natal life to an alteration of adipocyte production upon an incorrect diet style, which in turn would produce obesity.
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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".