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Record W1493151424 · doi:10.5772/19413

Cellular Restriction Factors: Exploiting the Body’s Antiviral Proteins to Combat HIV-1/AIDS

2011· book-chapter· en· W1493151424 on OpenAlexaff
N. Jenna, Jessica G.K., Joshua S. Clayton, Matthew Warren, Duncan Stephen

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)VirologyMedicineImmunology

Abstract

fetched live from OpenAlex

In 1983, when researchers first isolated HIV-1 from an AIDS patient, few imagined that it foretold a worldwide pandemic More than 25 years later, 65 million people have been infected with HIV-1; nearly half of these people have died of AIDS, and despite many scientific advances we are still without an efficacious vaccine The majority of HIV-1 infections and deaths have occurred in developing countries, with sub-Saharan Africa accounting for over 38 million HIV-1 infections alone. Sadly, the number of new infections currently exceeds our ability to treat everyone infected with the virus, and in the hardest-hit countries the social and economic backlash has been profound. After HIV-1 was isolated, a blood test to screen patients and the blood supply quickly followed, as did research on its structure and pathogenesis. Many assumed that a vaccine would be available in a few years, and excitement increased further with the licensing of the first effective drug against HIV-1, zidovudine (AZT) (Fischl et al., 1987). However, researchers soon discovered that the virus was highly resilient, and HIV-1 quickly developed resistance to AZT (Poli et al., 1989 Over the next few years, a number of new antiretroviral drugs were developed that attacked the virus in different ways, and it was at this time that a new approach to therapy ensued. Highly active antiretroviral therapy (HAART) combined three or more different drugs to reduce HIV-1 replication, and significantly improved the prognosis of HIV-1-infected individuals However, HAART was not a cure, and many patients were resistant to at least one of the antiretroviral drugs. In addition, the drugs were highly toxic, making adherence to treatment difficult. During this time, the vaccine field was also hard at work, trying to develop a safe and effective HIV-1 vaccine. Most initial vaccine approaches focused on the HIV-1 envelope protein (gp120), and aimed to induce an antibody response to gp120. AIDSVAX was the first vaccine candidate of this type, and was developed by a U.S. pharmaceutical company called VaxGen (Flynn et al., 2005 An alternative approach, developed by Merck, aimed to induce a T-cell response to HIV-1 using a recombinant adenovirus vector expressing HIV-1 Gag, Pol and Nef proteins (Shiver et al., 2002). Unfortunately, results from www.intechopen.com

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.548
Threshold uncertainty score1.000

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.007

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 head0.038
GPT teacher head0.247
Teacher spread0.209 · 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.

Study designBench or experimental
Domainnot available
GenreOther

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

Citations0
Published2011
Admission routes1
Has abstractyes

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