Evidence map›Paper›PMID 30384974›Full record

ReviewBiomaterials2019

In vitro and ex vivo systems at the forefront of infection modeling and drug discovery.

Di Shi, Gujie Mi, Mian Wang, Thomas J Webster

Abstract readReview
In one paragraph

Review in Biomaterials, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing 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

72 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Universal-BacMicrobiologyOpen · 2026
    Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Parkinson's-Linked LRRK2 and GBA1 Mutations Modulate the Peripheral Immune Response to Pseudomonas aeruginosa.Movement disorders : official journal of the Movement Disorder Society · 2026
    Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. StudyingPharmaceuticals (Basel, Switzerland) · 2025
    Review
  20. Article

12 more citing papers are in PubMed but not listed here.

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

4 authors.

Di ShiDepartment of Chemical Engineering, Northeastern University, Boston, MA 02115, USA.
Gujie MiDepartment of Chemical Engineering, Northeastern University, Boston, MA 02115, USA.
Mian WangDepartment of Chemical Engineering, Northeastern University, Boston, MA 02115, USA.
Thomas J WebsterDepartment of Chemical Engineering, Northeastern University, Boston, MA 02115, USA. Electronic address: th.webster@neu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial infections and antibiotic resistant bacteria have become a growing problem over the past decade. As a result, the Centers for Disease Control predict more deaths resulting from microorganisms than all cancers combined by 2050. Currently, many traditional models used to study bacterial infections fail to precisely replicate the in vivo bacterial environment. These models often fail to incorporate fluid flow, bio-mechanical cues, intercellular interactions, host-bacteria interactions, and even the simple inclusion of relevant physiological proteins in culture media. As a result of these inadequate models, there is often a poor correlation between in vitro and in vivo assays, limiting therapeutic potential. Thus, the urgency to establish in vitro and ex vivo systems to investigate the mechanisms underlying bacterial infections and to discover new-age therapeutics against bacterial infections is dire. In this review, we present an update of current in vitro and ex vivo models that are comprehensively changing the landscape of traditional microbiology assays. Further, we provide a comparative analysis of previous research on various established organ-disease models. Lastly, we provide insight on future techniques that may more accurately test new formulations to meet the growing demand of antibiotic resistant bacterial infections.

Indexed as

AnimalsAnti-Bacterial AgentsBacteriaBacterial InfectionsDrug DiscoveryEquipment DesignHumansInfectionsLab-On-A-Chip DevicesMicrobial Sensitivity TestsAnti-Bacterial AgentsEx vivoInfection modelsIn vitroNanotechnologyOrgan-on-a-chip

Identifiers

PMID30384974
PMCPMC7172914

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.