Distinct neutrophil counts and functions in newly diagnosed type 1 diabetes, latent autoimmune diabetes in adults, and type 2 diabetes
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Recent discoveries from animal models demonstrated that neutrophils can induce type 1 diabetes (T1D) through infiltrating into the islets. However, the evidence of their actions in T1D patients is relatively rare, and the change trend of neutrophil numbers and functions in different subtypes of diabetes has not been investigated. METHODS: Patients with newly diagnosed T1D (n = 189), latent autoimmune diabetes in adults (LADA) (n = 86), T2D (n = 235), and healthy controls (n = 709) were enrolled. Circulating neutrophil counts were measured, and their correlations with clinical parameters were analysed. Neutrophils were isolated by density gradient centrifugation and magnetic bead cell sorting method. Neutrophil migration rate and chemokine levels in the blood were explored by trans-well and ELISA, respectively. Neutrophil phagocytosis rate, adhesion molecules and chemokine receptors expression were investigated by flow cytometry. RESULTS: Compared with controls, neutrophil counts decreased in T1D patients but increased in T2D patients, with no change in LADA patients. The numbers showed a gradual increase trend from T1D, LADA to T2D. In autoimmune diabetes, neutrophil counts were associated with the number and titre of positive autoantibodies against β-cell antigens. No difference was found in neutrophil phagocytosis rate, but neutrophil migration in T1D patients was impaired and associated with CD62L expression, which was related closely to the titre of autoantibody. CONCLUSIONS: Neutrophil numbers and migration abilities displayed distinct levels in different types of diabetes. In T1D, CD62L seems to play an important role in the migration of neutrophils and β-cell autoimmunity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it