Evidence map›Paper›PMID 28659881›Full record

ArticleFrontiers in microbiology2017

RNA Profiling Analysis of the Serum Exosomes Derived from Patients with Active and Latent

Lingna Lv, Cuidan Li, Xiuli Zhang, Nan Ding, Tianshu Cao, Xinmiao Jia, Jinghui Wang, Liping Pan, Hongyan Jia, Zihui Li and 3 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Impact ofMicroorganisms · 2024
    Article
  5. Review
  6. Exosomal microRNAs associated with tuberculosis among people living with human immunodeficiency virus.Journal of clinical tuberculosis and other mycobacterial diseases · 2024
    Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Multimerin-1 and cancer: a review.Bioscience reports · 2022
    Review
  18. Extracellular Vesicles in Mycobacteria and Tuberculosis.Frontiers in cellular and infection microbiology · 2022
    Review
  19. Review
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Lingna LvBeijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical UniversityBeijing, China.
Cuidan LiCAS Key Laboratory of Genome Science and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.
Xiuli ZhangCAS Key Laboratory of Genome Science and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.
Nan DingCAS Key Laboratory of Genome Science and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.
Tianshu CaoCAS Key Laboratory of Genome Science and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.
Xinmiao JiaCAS Key Laboratory of Genome Science and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.
Jinghui WangBeijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical UniversityBeijing, China.
Liping PanBeijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical UniversityBeijing, China.
Hongyan JiaBeijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical UniversityBeijing, China.
Zihui LiBeijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical UniversityBeijing, China.
Ju ZhangCAS Key Laboratory of Genome Science and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.
Fei ChenCAS Key Laboratory of Genome Science and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.
Zongde ZhangBeijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical UniversityBeijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) has exceeded HIV as the most lethal infectious disease globally for two consecutive years. Moreover, one third of the world's population is estimated to have latent tuberculosis infection (LTBI). This is mainly because of difficulties associated with diagnosis and treatment for both TB and LTBI patients. Exosomes provide a promising research tool for TB diagnosis and treatment because they are released from various cells containing valuable biochemical information related to disease. In this study, we performed RNA-sequencing analysis on exosomes derived from clinical specimens of healthy controls (HC), active tuberculosis (ATB), and LTBI patients. Our results revealed the distinct gene expression profiles of the exosomes from LTBI and ATB patients. (1) We identified many distinct up-regulated and down-regulated differentially expressed genes (DEGs) in LTBI and ATB samples, and further screened the top-20 DEGs which might provide a potential panel for differentiation of HC, LTBI, and ATB. (2) We classified all the DEGs into six expression patterns, screened the top-20 genes in each pattern, and mainly focused on those highly expressed in LTBI and ATB. (3) Some

Indexed as

biomarkerexosomeIPAlatent tuberculosis infection (LTBI)Mycobacterium tuberculosis (Mtb)RNA sequencingtranscriptometuberculosis (TB)

Identifiers

PMID28659881
PMCPMC5466984

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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.