Evidence map›Paper›PMID 39336119›Full record

ReviewBiology2024

Roles of Toll-like Receptor Signaling in Inflammatory Bone Resorption.

Tsukasa Tominari, Chiho Matsumoto, Yuki Tanaka, Kensuke Shimizu, Masaru Takatoya, Moe Sugasaki, Kento Karouji, Urara Kasuga, Chisato Miyaura, Shinji Miyata and 3 more

Abstract readReview
In one paragraph

Review in Biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Review
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  12. Bone and Infections: An Osteoimmunological Interplay.International journal of molecular sciences · 2026
    Review
  13. Article
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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.

Tsukasa TominariDepartment of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.ORCID 0000-0001-5683-8951
Chiho MatsumotoDepartment of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.
Yuki TanakaCooperative Major of Advanced Health Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.
Kensuke ShimizuDepartment of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.ORCID 0009-0002-9103-7783
Masaru TakatoyaCooperative Major of Advanced Health Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.
Moe SugasakiCooperative Major of Advanced Health Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.
Kento KaroujiCooperative Major of Advanced Health Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.
Urara KasugaDepartment of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.
Chisato MiyauraDepartment of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.
Shinji MiyataInada Research Unit, Institute of Global Innovation Research, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.ORCID 0000-0001-6635-1645
Yoshifumi ItohInada Research Unit, Institute of Global Innovation Research, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.ORCID 0000-0002-2128-2823
Michiko HirataDepartment of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.
Masaki InadaDepartment of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo 184-8588, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toll-like receptors (TLRs) are pattern recognition receptors expressed in immune cells, including neutrophils, macrophages, and dendritic cells. Microbe-associated molecular patterns, including bacterial components, membranes, nucleic acids, and flagella are recognized by TLRs in inflammatory immune responses. Periodontal disease is an inflammatory disease known to cause local infections associated with gingival inflammation, subsequently leading to alveolar bone resorption. Prostaglandin E2 (PGE2) is a key mediator of TLR-induced inflammatory bone resorption. We previously reported that membrane-bound PGE synthase (mPGES-1)-deficient mice failed to induce bone resorption by lipopolysaccharide (LPS), a major pathogenic factor involved in periodontal bone resorption. Further experiments exploring specific pathogen-promoting osteoclast differentiation revealed that various TLR ligands induced osteoclast differentiation in a co-culture model. The ligands for TLR2/1, TLR2/6, TLR3, and TLR5, as well as TLR4, induce osteoclast differentiation associated with the production of PGE2 and the receptor activator of nuclear factor-kappa B ligand (RANKL), an inevitable inducer of osteoclast differentiation in osteoblasts. In vivo, local injection of TLR ligands, including TLR2/1, TLR2/6, and TLR3, resulted in severe alveolar bone resorption. This review summarizes the latest findings on TLR-mediated osteoclast differentiation and bone resorption in inflammatory diseases, such as periodontal diseases.

Indexed as

bone resorptioninnate immunityosteoblastsosteoclastsperiodontal diseaseprostaglandin E2Toll-like receptors

Identifiers

PMID39336119
PMCPMC11429252

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.