Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 440

The DOI matches its Crossref record; 171 of the 171 references it cites were found in a registry or an index.

Lipoproteins of Bacterial Pathogens

Open access
Kovacs-Simon, A., Titball, R. W., Michell, S. L.·2011·Infection and Immunity

Abstract

Bacterial lipoproteins are a set of membrane proteins with many different functions. Due to this broad-ranging functionality, these proteins have a considerable significance in many phenomena, from cellular physiology through cell division and virulence. Here we give a general overview of lipoprotein biogenesis and highlight examples of the roles of lipoproteins in bacterial disease caused by a selection of medically relevant Gram-negative and Gram-positive pathogens:Mycobacterium tuberculosis,Streptococcus pneumoniae,Borrelia burgdorferi, and Neisseria meningitidis. Lipoproteins have been shown to play key roles in adhesion to host cells, modulation of inflammatory processes, and translocation of virulence factors into host cells. As such, a number of lipoproteins have been shown to be potential vaccines. This review provides a summary of some of the reported roles of lipoproteins and of how this knowledge has been exploited in some cases for the generation of novel countermeasures to bacterial diseases.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1128/iai.00682-10

Cites

171 of 171 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

1 retracted

Show all 171 references

Cited by

See all 440

Metadata

Authors
Kovacs-Simon, A., Titball, R. W., & Michell, S. L.
Venue
Infection and Immunity
Published
2011-02
Volume
79
Issue
2
Pages
548-561
ISSN
  • 0019-9567 (ISSN-L)
  • 1098-5522
OpenAlex
W2052308056
Cited by
440
References
171
FWCI
18.01
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Lipoproteins of Bacterial Pathogens. https://app.cochat.ai/papers/10.1128/iai.00682-10
The paper
Kovacs-Simon, A., Titball, R. W., & Michell, S. L. (2011). Lipoproteins of Bacterial Pathogens. Infection and Immunity. https://doi.org/10.1128/iai.00682-10

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.