ReviewBio Systems2014
HIV-associated neuropathogenesis: a systems biology perspective for modeling and therapy.
Review in Bio Systems, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 11 citations in OpenAlex.
- Modeling brain lentiviral infections during antiretroviral therapy in AIDS.Journal of neurovirology · 2017Article
- HIV DNA Is Frequently Present within Pathologic Tissues Evaluated at Autopsy from Combined Antiretroviral Therapy-Treated Patients with Undetectable Viral Loads.Journal of virology · 2016Article
- Relevance of retrovirus quantification in cerebrospinal fluid for neurologic diagnosis.Journal of biomedical science · 2015Article
- Role of hexokinase-1 in the survival of HIV-1-infected macrophages.Cell cycle (Georgetown, Tex.) · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Despite the development of powerful antiretroviral drugs, HIV-1 associated neurological disorders (HAND) will affect approximately half of those infected with HIV-1. Combined anti-retroviral therapy (cART) targets viral replication and increases T-cell counts, but it does not always control macrophage polarization, brain infection or inflammation. Moreover, it remains difficult to identify those at risk for HAND. New therapies that focus on modulating host immune response by making use of biological pathways could prove to be more effective than cART for the treatment of neuroAIDS. Additionally, while numerous HAND biomarkers have been suggested, they are of little use without methods for appropriate data integration and a systems-level interpretation. Machine learning, could be used to develop multifactorial computational models that provide clinicians and researchers with the ability to identify which factors (in what combination and relative importance) are considered important to outcome.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.