ArticleBiomedical engineering online2021
Computational flow cytometric analysis to detect epidermal subpopulations in human skin.
Article in Biomedical engineering online, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 6 citations in OpenAlex.
- Development of a Spectral Flow Cytometry Analysis Pipeline for High-dimensional Immune Cell Characterization.Journal of immunology (Baltimore, Md. : 1950) · 2024Article
- Development of a Spectral Flow Cytometry Analysis Pipeline for High-Dimensional Immune Cell Characterization.bioRxiv : the preprint server for biology · 2024Article
- Isolation of Human Progenitor Epidermal Cells on Collagen Type IV and Analysis of Their Markers with Flow Cytometry and PCR Methods.Methods in molecular biology (Clifton, N.J.) · 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
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe detection and dissection of epidermal subgroups could lead to an improved understanding of skin homeostasis and wound healing. Flow cytometric analysis provides an effective method to detect the surface markers of epidermal cells while producing high-dimensional data files.
methodsA 9-color flow cytometric panel was optimized to reveal the heterogeneous subgroups in the epidermis of human skin. The subsets of epidermal cells were characterized using automated methods based on dimensional reduction approaches (viSNE) and clustering with Spanning-tree Progression Analysis of Density-normalized Events (SPADE).
resultsThe manual analysis revealed differences in epidermal distribution between body sites based on a series biaxial gating starting with the expression of CD49f and CD29. The computational analysis divided the whole epidermal cell population into 25 clusters according to the surface marker phenotype with SPADE. This automatic analysis delineated the differences between body sites. The consistency of the results was confirmed with PhenoGraph.
conclusionA multicolor flow cytometry panel with a streamlined computational analysis pipeline is a feasible approach to delineate the heterogeneity of the epidermis in human skin.
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.