Evidence map›Paper›PMID 32601967›Full record

ReviewCurrent topics in microbiology and immunology2021

Human Three-Dimensional Models for Studying Skin Pathogens.

Elena Boero, Malgorzata Ewa Mnich, Andrea Guido Oreste Manetti, Elisabetta Soldaini, Luca Grimaldi, Fabio Bagnoli

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current topics in microbiology and immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
4.6field-weighted citation impact, top 5% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. 3D human epithelial models: a promising platform for studyingFrontiers in cellular and infection microbiology · 2025
    Article
  2. Article
  3. Review
  4. Frontiers in immunology · 2021
    Article
  5. Frontiers in immunology · 2021
    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

6 authors at 1 institution in 1 country.

Elena BoeroGSK, Siena, Italy.
Malgorzata Ewa MnichGSK, Siena, Italy.
Andrea Guido Oreste ManettiGSK, Siena, Italy.
Elisabetta SoldainiGSK, Siena, Italy.
Luca GrimaldiDepartment of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
Fabio BagnoliGSK, Siena, Italy. fabio.x.bagnoli@gsk.com.
University of Siena · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skin is the most exposed surface of the human body, separating the microbe-rich external environment, from the sterile inner part. When skin is breached or its homeostasis is perturbed, bacterial, fungal and viral pathogens can cause local infections or use the skin as an entry site to spread to other organs. In the last decades, it has become clear that skin provides niches for permanent microbial colonization, and it actively interacts with microorganisms. This crosstalk promotes skin homeostasis and immune maturation, preventing expansion of harmful organisms. Skin commensals, however, are often found to be skin most prevalent and dangerous pathogens. Despite the medical interest, mechanisms of colonization and invasion for most skin pathogens are poorly understood. This limitation is due to the lack of reliable skin models. Indeed, animal models do not adequately mimic neither the anatomy nor the immune response of human skin. Human 3D skin models overcome these limitations and can provide new insights into the molecular mechanisms of microbial pathogenesis. Herein, we address the strengths and weaknesses of different types of human skin models and we review the main findings obtained using these models to study skin pathogens.

Indexed as

BacteriaFungiAnimalsHumansSymbiosis

Identifiers

PMID32601967
OpenAlexW3038532617

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.