ArticleCells2024
Comparison of the Single Cell Immune Landscape between Subjects with High
Article in Cells, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 6 citations in OpenAlex.
- Deciphering the different Mycobacterium avium complex infections of HIV and non-HIV patients by bacterial GWAS and immune cells flow cytometry.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Article
- Multidimensional cfRNA response modeling identifies a 5-gene pair signature for high-robust pulmonary tuberculosis diagnosis.iScience · 2026Article
- Functional analysis of distinct factors linked to the development of latent to active tuberculosis.Frontiers in cellular and infection microbiology · 2026Review
- Cytotoxic granules and effector molecules from immune cells in tuberculosis: Mechanisms of host defense and therapeutic potential.Virulence · 2025Review
- Transcriptomic and proteomic signatures of host NK cells delineate distinct immune states across tuberculosis infection statuses.Frontiers in immunology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
It is unclear how the immune system controls the transition from latent tuberculosis (TB) infection (LTBI) to active pulmonary infection (PTB). Here, we applied mass spectrometry cytometry time-of-flight (CyTOF) analysis of peripheral blood mononuclear cells to compare the immunological landscapes in patients with high tuberculous bacillary load PTB infections and LTBI. A total of 32 subjects (PTB [n = 12], LTBI [n = 17], healthy volunteers [n = 3]) were included. Participants with active PTBs were phlebotomized before administering antituberculosis treatment, whereas participants with LTBI progressed to PTB at the time of household screening. In the present study, CyTOF analysis identified significantly higher percentages of mucosal-associated invariant natural killer T (MAIT NKT) cells in subjects with LTBI than in those with active PTB and healthy controls. Moreover, 6 of 17 (35%) subjects with LTBI progressed to active PTB (LTBI progression) and had higher proportions of MAIT NKT cells and early NKT cells than those without progression (LTBI non-progression). Subjects with LTBI progression also showed a tendency toward low B cell levels relative to other subject groups. In conclusion, MAIT NKT cells were substantially more prevalent in subjects with LTBI, particularly those with progression to active PTB.
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.