d-Amino Acids and Classical Neurotransmitters in Healthy and Type 2 Diabetes-Affected Human Pancreatic Islets of Langerhans
Bibliographic record
Abstract
The pancreatic islets of Langerhans are clusters of cells that function as endocrine units synthesizing and releasing insulin and a range of additional peptide hormones. The structural and chemical characteristics of islets change during type 2 diabetes development. Although a range of metabolites including neurotransmitters has been reported in rodent islets, the involvement of these cell-to-cell signaling molecules within human pancreatic islets in the pathophysiology of type 2 diabetes is not well known, despite studies suggesting that these molecules impact intra- and inter-islet signaling pathways. We characterize the enigmatic cell-to-cell signaling molecules, d-serine (d-Ser) and d-aspartate (d-Asp), along with multiple classical neurotransmitters and related molecules, in healthy versus type 2 diabetes-affected human islets using capillary electrophoresis separations. Significantly reduced d-Ser percentage and gamma-aminobutyric acid (GABA) levels were found in type 2 diabetes-affected islets compared to healthy islets. In addition, the negative correlations of many of the signaling molecules, such as d-Ser percentage (r = -0.35), d-Asp (r = -0.32), serotonin (r = -0.42), and GABA (r = -0.39) levels, with hemoglobin A1c (HbA1c) levels and thus with the progression of type 2 diabetes further demonstrate the disruption in intra- or inter-islet signaling pathways and suggest that these cell-to-cell signaling molecules may be potential therapeutic targets.
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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 | 0.000 | 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) | 0.000 | 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".