Selected Thiadiazine-Thione Derivatives Attenuate Neuroinflammation in Chronic Constriction Injury Induced Neuropathy
Bibliographic record
Abstract
Neuropathic pain refers to a lesion or disease of peripheral and/or central somatosensory neurons and is an important body response to actual or potential nerve damage. We investigated the therapeutic potential of two thiadiazine-thione [TDT] derivatives, 2-(5-propyl-6-thioxo-1, 3, 5-thiadiazinan-3-yl) acetic acid [TDT1] and 2-(5-propyl-2-thioxo-1, 3, 5-thiadiazinan-3-yl) acetic acid [TDT2] against CCI (chronic constriction injury)-induced neuroinflammation and neuropathic pain. Mice were used for assessment of acute toxicity of TDT derivatives and no major toxic/bizarre responses were observed. Anti-inflammatory activity was assessed using the carrageenan test, and both TDT1 and TDT2 significantly reduced carrageenan-induced inflammation. We also used rats for the induction of CCI and performed allodynia and hyperalgesia-related behavioral tests followed by biochemical and morphological analysis using RT-qPCR, immunoblotting, immunohistochemistry and immunofluorescence. Our findings revealed that CCI induced clear-cut allodynia and hyperalgesia which was reversed by TDT1 and TDT2. To determine the function of TDT1 and TDT2 in glia-mediated neuroinflammation, Iba1 mRNA and protein levels were measured in spinal cord tissue sections from various experimental groups. Interestingly, TDT1 and TDT2 substantially reduced the mRNA expression and protein level of Iba1, implying that TDT1 and TDT2 may mitigate CCI-induced astrogliosis. In silico molecular docking studies predicted that both compounds had an effective binding affinity for TNF-α and COX-2. The compounds interactions with the proteins were dominated by both hydrogen bonding and van der Waals interactions. Overall, these results suggest that TDT1 and TDT2 exert their neuroprotective and analgesic potentials by ameliorating CCI-induced allodynia, hyperalgesia, neuroinflammation and neuronal degeneration in a dose-dependent manner.
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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) | 0.000 | 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 | 0.001 |
| 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".