Progress in Clinical Neurosciences: The Neuropathogenesis of HIV Infection: Host-Virus Interaction and the Impact of Therapy
Bibliographic record
Abstract
Despite the availability of highly active antiretroviral therapy (HAART), primary HIV-related neurological diseases remain major problems in HIV clinics. The present review examines the pathogenesis of HIV-related dementia and the less severe minor cognitive and motor deficit, together with distal sensory and drug-induced toxic polyneuropathies. Abnormal host immune responses within the nervous system and the role of viral expression and diversity are emphasized in relation to neurovirulence. Induction of innate immune responses within the central and peripheral nervous systems, largely mediated by cells of macrophage lineage, appear to be common to the development of primary HIV-related neurological disease. Activation of these cell types results in the release of a cascade of inflammatory molecules including cytokines, chemokines, matrix metalloproteinases, and arachidonic acid metabolites that influence neuronal survival. Individual viral proteins encoded by envelope and tat genes and discrete sequences within these genes influence the extent to which these pro-inflammatory molecules are induced. At the same time, systemic immune suppression may influence the occurrence and severity of HIV-related neurological diseases. Implementation of HAART and neuroprotective treatments improves neurological function although the evolution of drug-resistant viral strains limits the sustained benefits of HAART.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".