Circulating progenitor and angiogenic cell frequencies are abnormally static over pregnancy in women with preconception diabetes: A pilot study
Bibliographic record
Abstract
Type 1 and 2 diabetes decrease the frequencies and functional capacities of circulating angiogenic cells (CAC). Diabetes also elevates gestational complications. These observations may be interrelated. We undertook pilot studies to address the hypothesis that preconception diabetes deviates known gestational increases in CACs. Cross-sectional study of type 1 diabetic, type 2 diabetic and normoglycemic pregnant women was conducted at 1st, 2nd, and 3rd trimester and compared to a 6mo postpartum surrogate baseline. Circulating progenitor cells (CPC; CD34+CD45dimSSlow) and CACs (CD34+CD45dimSSlow expressing CD133 without or with KDR) were quantified by flow cytometry and by colony assay (CFU-Hill). In pregnant normoglycemic women, CD34+CD45dimSSlow cell frequency was greater in 1st and 3rd trimester than postpartum but frequency of these cells was static over type 1 or 2 diabetic pregnancies. Type 1 and type 2 diabetic women showed CACs variance versus normal controls. Type 1 diabetic women had more total CD34+KDR+ CACs in 1st trimester and a higher ratio of CD133+KDR+ to total CD133+ cells in 1st and 2nd trimesters than control women, demonstrating an unbalance in CD133+KDR+ CACs. Type 2 diabetic women had more CD133+KDR+ CACs in 1st trimester and fewer CD133+KDR- CACs at mid-late pregnancy than normal pregnant women. Thus, pregnancy stage-specific physiological fluctuation in CPCs (CD34+) and CACs (CD133+KDR+ and CD133+KDR-) did not occur in type 1 and type 2 diabetic women. Early outgrowth colonies were stable across normal and diabetic pregnancies. Therefore, preconception diabetes blocks the normal dynamic pattern of CAC frequencies across gestation but does not alter colony growth. The differences between diabetic and typical women were seen at specific gestational stages that may be critical for initiation of the uterine vascular pathologies characterizing diabetic gestations.
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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 | 0.001 |
| 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".