Neurobehavioral Performance in Feline Immunodeficiency Virus Infection: Integrated Analysis of Viral Burden, Neuroinflammation, and Neuronal Injury in Cortex
Bibliographic record
Abstract
Human immunodeficiency virus (HIV) infection causes motor and neurocognitive abnormalities affecting >50% of children and 20% of adults with HIV/AIDS (acquired immunodeficiency syndrome). The closely related lentivirus, feline immunodeficiency virus (FIV), also causes neurobehavioral deficits. Herein, we investigated the extent to which FIV infection affected specific motor and cognitive tasks in conjunction with viral burden and immune responses within the brain. Neonatal animals were infected with a neurovirulent FIV strain (FIV-Ch) and assessed in terms of systemic immune parameters, viral burden, neurobehavioral performance, and neuropathological features. FIV-infected animals displayed less weight gain and lower blood CD4(+) T-cell levels than mock-infected animals (p < 0.05). Gait analyses disclosed greater gait width with increased variation in FIV-infected animals (p < 0.05). Maze performance showed that FIV-infected animals were slower and made more navigational errors than mock-infected animals (p < 0.05). In the object memory test, the FIV-infected group exhibited fewer successful steps with more trajectory errors compared with the mock-infected group (p < 0.05). Performance on the gait, maze, and object memory tests was inversely correlated with F4/80 and CD3 epsilon expression (p < 0.05) and with viral burden in parietal cortex (p < 0.05). Amino acid analysis in cortex showed that D-serine levels were reduced in FIV-infected animals, which was accompanied by diminished kainate and AMPA receptor subunit expression (p < 0.05). The neurobehavioral findings in FIV-infected animals were associated with increased gliosis and reduced cortical neuronal counts (p < 0.05). The present studies indicated that specific motor and neurocognitive abilities were impaired in FIV infection and that these effects were closely coupled with viral burden, neuroinflammation, and neuronal loss.
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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".