Autoimmune-Induced Pain Alters Affective Behaviors in a Model of Neuropsychiatric Lupus?
Bibliographic record
Abstract
As commonly seen in patients with neuropsychiatric systemic lupus erythematosus (NP-SLE), spontaneous disease onset in the MRL/MpJ-Faslpr/J (MRL-lpr) mouse model of NP-SLE is accompanied by increased autoantibodies, pro-inflammatory cytokines and behavioral dysfunction which precede neuroinflammation and structural brain lesions. Given that P2X purine receptors are important in peripheral "pain" signaling, the possibility that purinoception is involved in the development of aberrant affective behaviors was explored in the present study. Suramin, a P2X purinoceptor antagonist, was administered to lupus-prone mice from 5 to 14 weeks of age (60 mg/kg, i.p.). Novel object and sucrose preference tests were performed to examine behavior, and enzyme-linked immunosorbant assays for autoantibodies and pro-inflammatory cytokines were employed in immunopathological analyses. Suramin was found to attenuate markers of autoimmunity and inflammation, but was not immunosuppressive. Treatment did, however, prevent neophobic- and anhedonic-like deficits in MRL-lpr mice. More specifically, animals receiving the drug showed a profound 3-fold increase in their responsiveness to palatable solution (i.e. a reversal of anhedonia) and were less "distressed" by novelty. The present data supports the hypothesis that sustained activation of the peripheral immune system induces nociceptive-related behavioral symptomatology in lupus animals which is attenuated by the analgesic effects of suramin. It is proposed that anti-purine or cross-reactive autoantibodies cause neuronal hyperexcitability within "pain" pathways early in the disease process, which manifests as affective deficits. At a later stage of chronic lupus-like disease (following breakdown of the blood-brain barrier), fixed structural lesions in dopaminergic pathways likely account for and maintain impairments in emotionality.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".