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Evaluation of the human herpesvirus 8 DNA load in blood and Kaposi's sarcoma skin lesions from AIDS Patients on highly active antiretroviral therapy

2000· article· en· W2010871174 on OpenAlexaff
Guy Boivin, Annie Gaudreau, Jean‐Pierre Routy

Bibliographic record

VenueAIDS · 2000
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsFonds de Recherche du Québec - SantéCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsViral loadPeripheral blood mononuclear cellKaposi's sarcomaMedicineSarcomaViral diseasePathologyImmunopathologyImmunologyVirusHuman herpesvirusBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the human herpesvirus 8 (HHV-8) DNA load in peripheral blood mononuclear cells (PBMC) and Kaposi's sarcoma (KS) skin lesions of subjects with AIDS and to correlate these measures with the tumour load. DESIGN: Assessment of the HHV-8 DNA load was performed every 3 months in PBMC and every 6 months in KS skin lesions from seven subjects with AIDS who were receiving highly active antiretroviral therapy (HAART). METHODS: The HHV-8 DNA load was determined by a quantitative-competitive PCR using 0.2 microg of DNA from PBMC or KS skin biopsies. Staging of KS was performed by evaluating the number and type of cutaneous KS lesions. RESULTS: The three subjects with the most extensive and active (nodular) KS had the highest amounts of HHV-8 DNA in KS skin lesions and the lowest CD4 T cell counts (< 200 x 10(6)/l). In contrast, the four other subjects with regressing KS while on HAART had a low viral load in their KS lesions. All but one subject who also had multicentric Castleman's disease had low amounts of HHV-8 DNA in PBMC. CONCLUSION: There is a strong relationship between the tumour burden and the HHV-8 viral load in KS skin lesions of subjects with AIDS, reinforcing the causal link between this herpesvirus and AIDS-related KS.

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.

How this classification was reachedexpand

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.520

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 head0.020
GPT teacher head0.286
Teacher spread0.266 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations59
Published2000
Admission routes1
Has abstractyes

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