Quantitative profiling of neurotransmitter abnormalities in brain, cerebrospinal fluid, and serum of experimental diabetic encephalopathy male rat
Bibliographic record
Abstract
Diabetic encephalopathy (DE), one of the most prevalent chronic complications of diabetes mellitus, is short of effective prevention and formidable therapeutic strategies. The aim of the present study is to reveal the imbalance of tryptophan (Trp) and its metabolites in streptozotocin (STZ)-induced experimental DE rats to underscore their critical values in clinical diagnosis of the disease. For this purpose, we first developed an accurate and appropriate simultaneous method for measuring Trp and its metabolites using liquid chromatography-tandem mass spectrometry, which was in accordance with the requirements of biological sample analysis. Secondly, a single STZ intraperitoneal injection was administered to male Sprague-Dawley rats, and their cognitive function was detected by Morris water maze tests. Cerebrospinal fluid (CSF), serum, and brain tissue were then collected for the determination of Trp and its metabolites. Compared with age-matched control rats, the levels of neuroprotective serotonin decreased significantly in the samples of cortices, hippocampi, striatum, CSF, and serums in the STZ-induced DE rats, while the levels of neurotoxic 3-hydroxykynurenine increased significantly. Moreover, analogous changes of both compounds were found in the central nervous system and peripheral blood of the STZ-induced DE rats. In conclusion, we established a quantitative method for the simultaneous detection of Trp and its metabolites, and we also present a critical elucidation of the nervous system dysfunction in DE.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".