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Record W2037581885 · doi:10.1186/1750-9378-5-s1-a77

The HIV nef protein within ARL is genetically and structurally distinct from those in the brain of patients with HAD

2010· article· en· W2037581885 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInfectious Agents and Cancer · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsAIDS Vancouver
Fundersnot available
KeywordsMedicineDiseaseImmunologyHuman immunodeficiency virus (HIV)PopulationVirologyMacrophageDementiaLymphomaViral diseaseBiologyPathologyGenetics

Abstract

fetched live from OpenAlex

Despite antiretroviral therapy, macrophages remain significant cellular reservoirs for HIV infection. Two fatal macrophage-mediated diseases still occur at a much higher rate in the HIV-infected and HAART-treated population: (1) AIDS-related lymphoma (ARL), a noninflammatory disease, and (2) HIV-associated dementia (HAD), an inflammatory disease. The frequency of HIV-infected macrophages in ARL is 50%. Macrophages are the primary HIV-infected cells in the brain. The mechanisms that lead to the development of these diseases are not understood. Because certain subtypes of HIV are associated with a higher prevalence of HAD, a viral genetic determinant for HAD development is likely. On the other hand, ARL development occurs fairly consistently across multiple HIV subtypes and genetic analysis has clearly differentiated ARL tissue-associated HIV from non-ARL tissue HIV within individuals. These facts raise two questions: (1) Are there tumor-specific genetic differences among HIV proteins that could influence the macrophage to accelerate ARL development? (2) How might HAD-associated and ARL-associated viruses differ at the genetic and structural levels? Our goal was to analyze HAD and ARL viral sequences and determine whether a disease association could be identified within viral proteins. The AIDS and Cancer Specimen Resource (ACSR) archives tissue samples derived from well-documented cases of both ARL and HAD. Multisite autopsies of 7 patients with ARL, HAD, and other neurological and systemic disorders were identified at the ACSR. More than 20 sequences from each of 5 to 7 tissues from each patient were sequenced. The HIV nef sequence was used in multiple genetic analyses, including a neural net signature pattern analysis, a tertiary structural analysis, and an analysis of the stability of an HIV viral microRNA associated with apoptosis. Signature pattern analysis clearly separated ARL from HAD viruses and identified positions that may in concert produce specific pathological outcomes. HIV subtype D viruses are known to be associated with a high rate of HAD. Comparative tertiary structural analysis of nef showed that HAD viruses were more similar to HIV subtype D viruses than ARL viruses. ARL viruses were either missing or possessed a less stable miR-H1 structure compared to HAD viruses. Our results show that HIV-associated diseases are likely related to specific viral genetic signatures and structures. Discovery of an ARL virus would enable the development of diagnostic tools and identify subsets of viruses to be targeted with drugs or vaccines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.245
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it