ReviewCells2023
Single-Cell Transcriptomics of
Review in Cells, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 7 citations in OpenAlex.
- Early immune dysregulation iniScience · 2026Article
- The study of immunological markers in tuberculosis across animal models and its translation to human research.Lab animal · 2026Review
- Persistent Increased Plasmacytoid Dendritic Cells and Inflammation in People With HIV Years After Tuberculosis.The Journal of infectious diseases · 2026Article
- Changing epidemiological patterns of tuberculosis in China from 1990 to 2023: trends and future projections of drug-resistant and HIV-associated tuberculosis.Frontiers in public health · 2026Article
- Advances in the Diagnosis of Latent Tuberculosis Infection.Infection and drug resistance · 2025Review
- Single-cell sequencing: Current applications in various tuberculosis specimen types.Cell proliferation · 2024Review
- Toll-Like Receptor Genes and Risk of Latent Tuberculosis Infection in People Infected with HIV-1.Viruses · 2024Article
- T Cell Responses during Human Immunodeficiency Virus/Vaccines · 2024Review
- Innovative aspects and applications of single cell technology for different diseases.American journal of cancer research · 2024Review
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 4 institutions in 1 country.
Funding
Abstract
Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) co-infection continues to pose a significant healthcare burden. HIV co-infection during TB predisposes the host to the reactivation of latent TB infection (LTBI), worsening disease conditions and mortality. There is a lack of biomarkers of LTBI reactivation and/or immune-related transcriptional signatures to distinguish active TB from LTBI and predict TB reactivation upon HIV co-infection. Characterizing individual cells using next-generation sequencing-based technologies has facilitated novel biological discoveries about infectious diseases, including TB and HIV pathogenesis. Compared to the more conventional sequencing techniques that provide a bulk assessment, single-cell RNA sequencing (scRNA-seq) can reveal complex and new cell types and identify more high-resolution cellular heterogeneity. This review will summarize the progress made in defining the immune atlas of TB and HIV infections using scRNA-seq, including host-pathogen interactions, heterogeneity in HIV pathogenesis, and the animal models employed to model disease. This review will also address the tools needed to bridge the gap between disease outcomes in single infection vs. co-infection. Finally, it will elaborate on the translational benefits of single-cell sequencing in TB/HIV diagnosis in humans.
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.