Not Only Glycaemic But Also Other Metabolic Factors Affect T Regulatory Cell Counts and Proinflammatory Cytokine Levels in Women with Type 1 Diabetes
Bibliographic record
Abstract
Type 1 diabetic (T1D) patients suffer from insulinopenia and hyperglycaemia. Studies have shown that if a patient's hyperglycaemic environment is not compensated, it leads to complex immune dysfunctions. Similarly, T1D mothers with poor glycaemic control exert a negative impact on the immune responses of their newborns. However, questions concerning the impact of other metabolic disturbances on the immune system of T1D mothers (and their newborns) have been raised. To address these questions, we examined 28 T1D women in reproductive age for the relationship between various metabolic, clinical, and immune parameters. Our study revealed several unexpected correlations which are indicative of a much more complex relationship between glucose and lipid factors (namely, glycosylated haemoglobin Hb1Ac, the presence of one but not multiple chronic diabetic complications, and atherogenic indexes) and proinflammatory cytokines (IL-1alpha and TNF-alpha). Regulatory T cell counts correlated with HbA1c, diabetic neuropathy, lipid spectra parameters, and IL-6 levels. Total T-helper cell count was interconnected with BMI and glycaemia variability correlated with lipid spectra parameters, insulin dose, and vitamin D levels. These and other correlations revealed in this study provide broader insight into the association of various metabolic abnormalities with immune parameters that may impact T1D mothers or their developing child.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".