ReviewVaccine2015
Understanding immune protection against tuberculosis using RNA expression profiling.
Review in Vaccine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 10 citations in OpenAlex.
- Prediction of tuberculosis treatment outcomes using biochemical makers with machine learning.BMC infectious diseases · 2025Article
- Distinct gene expression signatures comparing latent tuberculosis infection with different routes of Bacillus Calmette-Guérin vaccination.Nature communications · 2023Article
- Challenges of Diagnosing Mendelian Susceptibility to Mycobacterial Diseases in South Africa.International journal of molecular sciences · 2023Review
- Functional Analysis of Immune Signature Genes in Th1* Memory Cells Links ISOC1 and Pyrimidine Metabolism to IFN-γ and IL-17 Production.Journal of immunology (Baltimore, Md. : 1950) · 2021Article
- Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8Frontiers in medicine · 2021Article
- The TAM-TB Assay-A Promising TB Immune-Diagnostic Test With a Potential for Treatment Monitoring.Frontiers in pediatrics · 2019Article
- Construction and analysis of the transcription factor-microRNA co-regulatory network response toAmerican journal of translational research · 2017Article
- Severe Tuberculosis in Humans Correlates Best with Neutrophil Abundance and Lymphocyte Deficiency and Does Not Correlate with Antigen-Specific CD4 T-Cell Response.Frontiers in immunology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
A major limitation in the development and testing of new tuberculosis (TB) vaccines is the current inadequate understanding of the nature of the immune response required for protection against either infection with Mycobacterium tuberculosis (MTB) or progression to disease. Genome wide RNA expression analysis has provided a new tool with which to study the inflammatory and immunological response to mycobacteria. To explore how currently available transcriptomic data might be used to understand the basis of protective immunity to MTB, we analysed and reviewed published RNA expression studies to (1) identify a "susceptible" immune response in patients with acquired defects in the interferon gamma pathway; (2) identify the "failing" transcriptomic response in patients with TB as compared with latent TB infection (LTBI); and (3) identify elements of the "protective" response in healthy latently infected and healthy uninfected individuals.
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.