Evidence map›Paper›PMID 33764175›Full record

ReviewJournal of dental research2021

From Bite to Byte: Dental Structures Resolved at a Single-Cell Resolution.

R Fresia, P Marangoni, T Burstyn-Cohen, A Sharir

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of dental research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

18 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Identification of a Force-Induced Sox9Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  4. KMT2D Regulates Tooth Enamel Development.Journal of dental research · 2025
    Article
  5. Article
  6. KMT2D regulates tooth enamel development.bioRxiv : the preprint server for biology · 2024
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. 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

4 authors at 2 institutions in 2 countries.

R FresiaThe Institute of Dental Sciences, Faculty of Dental Medicine, Hebrew University, Jerusalem, Israel.
P MarangoniProgram in Craniofacial Biology and Department of Orofacial Sciences, University of California, San Francisco, CA, USA.
T Burstyn-CohenThe Institute of Dental Sciences, Faculty of Dental Medicine, Hebrew University, Jerusalem, Israel.
A SharirThe Institute of Dental Sciences, Faculty of Dental Medicine, Hebrew University, Jerusalem, Israel.
Hebrew University of Jerusalem · ILUniversity of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The systematic classification of the cells that compose a tissue or an organ is key to understanding how these cells cooperate and interact as a functional unit. Our capacity to detect features that define cell identity has evolved from morphological and chemical analyses, through the use of predefined genetic markers, to unbiased transcriptomic and epigenetic profiling. The innovative technology of single-cell RNA sequencing (scRNA-seq) enables transcriptional profiling of thousands of individual cells. Since its development, scRNA-seq has been extensively applied to numerous organs and tissues in a wide range of animal models and human samples, thereby providing a plethora of fundamental biological insights into their development, homeostasis, and pathology. In this review, we present the findings of 3 recent studies that employed scRNA-seq to unravel the complexity of cellular composition in mammalian teeth. These findings offer an unprecedented catalogue of cell types in the mouse incisor, which is a convenient model system for studying continuous tooth growth. These studies identified novel cell types in the tooth epithelium and mesenchyme, as well as new markers for known cell types. Computational analyses of the data also uncovered the lineage and dynamics of cell states during ameloblast and odontoblast differentiation during both normal homeostasis and injury repair. The transcriptional differences between the mouse incisor and mouse and human molars uncover species-specific as well as shared features in tooth cell composition. Here, we highlight these findings and discuss important similarities and differences between these studies. We also discuss potential future applications of scRNA-seq in dental research and dentistry. Together, these studies demonstrate how the rapidly evolving technology of scRNA-seq can advance the study of tooth development and function and provide putative targets for regenerative approaches.

Indexed as

Single-Cell AnalysisTranscriptomeAnimalsCell DifferentiationGene Expression ProfilingGenetic MarkersMiceSequence Analysis, RNAGenetic Markerscell differentiationregenerationsequence analysissingle-cell analysisstem cellstooth components

Identifiers

PMID33764175
PMCPMC8293759
OpenAlexW3135974087

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.