ReviewInternational journal of molecular sciences2023
Decoding the Human Epidermal Complexity at Single-Cell Resolution.
Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed.
- A single-cell multi-omics atlas of human eyelid skin.Frontiers in genetics · 2026Article
- Review
- Review
- Microbial metabolites control self-renewal and precancerous progression of human cervical stem cells.Nature communications · 2025Article
- Single-cell RNA sequencing reveals the impaired epidermal differentiation and pathological microenvironment in diabetic foot ulcer.Burns & trauma · 2025Article
- Biochemical characterization of the feedforward loop between CDK1 and FOXM1 in epidermal stem cells.Biology direct · 2024Article
- Coordinating energy metabolism and signaling pathways in epithelial self-renewal and differentiation.Biology direct · 2024Review
- Biochemical role of FOXM1-dependent histone linker H1B in human epidermal stem cells.Cell death & disease · 2024Article
- Deciphering "Immaturity-Stemness" in Human Epidermal Stem Cells at the Levels of Protein-Coding and Non-Coding Genomes: A Prospective Computational Approach.International journal of molecular sciences · 2024Article
- Allele-specific CRISPR-Cas9 editing of dominant epidermolysis bullosa simplex in human epidermal stem cells.Molecular therapy : the journal of the American Society of Gene Therapy · 2024Article
- FGF7 and FGF10 Promote Fate Transition of Human Epidermal Cell-derived Organoids to an Eccrine Gland Phenotype.International journal of biological sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The epidermis is one of the largest tissues in the human body, serving as a protective barrier. The basal layer of the epidermis, which consists of epithelial stem cells and transient amplifying progenitors, represents its proliferative compartment. As keratinocytes migrate from the basal layer to the skin surface, they exit the cell cycle and initiate terminal differentiation, ultimately generating the suprabasal epidermal layers. A deeper understanding of the molecular mechanisms and pathways driving keratinocytes' organization and regeneration is essential for successful therapeutic approaches. Single-cell techniques are valuable tools for studying molecular heterogeneity. The high-resolution characterization obtained with these technologies has identified disease-specific drivers and new therapeutic targets, further promoting the advancement of personalized therapies. This review summarizes the latest findings on the transcriptomic and epigenetic profiling of human epidermal cells, analyzed from human biopsy or after in vitro cultivation, focusing on physiological, wound healing, and inflammatory skin conditions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.