Lentivirus Infection Causes Neuroinflammation and Neuronal Injury in Dorsal Root Ganglia: Pathogenic Effects of STAT-1 and Inducible Nitric Oxide Synthase
Bibliographic record
Abstract
Distal sensory polyneuropathy (DSP) is currently the most common neurological complication of HIV infection in the developed world and is characterized by sensory neuronal injury accompanied by inflammation, which is clinically manifested as disabling pain and gait instability. We previously showed that feline immunodeficiency virus (FIV) infection of cats caused DSP together with immunosuppression in cats, similar to that observed in HIV-infected humans. In this study, we investigated the pathogenic mechanisms underlying the development of FIV-induced DSP using feline dorsal root ganglia (DRG) cultures, consisting of neurons, Schwann cells, and macrophages. FIV-infected cultures exhibited viral Ags (p24 and envelope) in macrophages accompanied by neuronal injury, indicated by neurite retraction, neuronal loss and decreased soma size, compared with mock-infected (control) cultures. FIV infection up-regulated inducible NO synthase (iNOS), STAT-1, and TNF-alpha mRNA levels in DRG cultures. Increased STAT-1 and iNOS mRNA levels were also observed in DRGs from FIV-infected animals relative to mock-infected controls. Similarly, immunolabeling studies of DRGs from FIV-infected animals showed that macrophages were the principal sources of STAT-1 and iNOS protein production. The iNOS inhibitor aminoguanidine reduced nitrotyrosine and protein carbonyl levels, together with preventing neuronal injury in FIV-infected DRG cultures. The present studies indicate that FIV infection of DRGs directly contributes to axonal and neuronal injury through a mechanism involving macrophage immune activation, which is mediated by STAT-1 and iNOS activation.
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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 | 0.000 |
| 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".