Evidence map›Paper›PMID 35586317›Full record

ArticleSTAR protocols2022

Isolation of five different primary cell types from a single sample of human skin.

Sylwia Kabacik, Donna Lowe, Howard Cohen, Sarah Felton, Joseph Spitzer, Ken Raj

Open access · goldAbstract read
In one paragraph

Article in STAR protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 37% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
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

6 authors at 2 institutions in 1 country.

Sylwia KabacikRadiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, UK Health Security Agency, Chilton, Didcot, OX11 0RQ Oxfordshire, UK.
Donna LoweRadiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, UK Health Security Agency, Chilton, Didcot, OX11 0RQ Oxfordshire, UK.
Howard CohenElizabeth House, 515 Limpsfield Road, Warlingham, CR6 9LF Surrey, UK.
Sarah FeltonOxford University Hospitals NHS Foundation Trust, Old Road, OX3 7LJ Oxford, UK.
Joseph SpitzerThe Surgery, 62 Cranwich Road, N16 5JF London, UK.
Ken RajRadiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, UK Health Security Agency, Chilton, Didcot, OX11 0RQ Oxfordshire, UK.
UK Health Security Agency · GBOxford University Hospitals NHS Trust · GB

Funding

Department of Health
6 · The paper itself

Abstract

We have developed a technique to isolate primary keratinocytes, melanocytes, fibroblasts, preadipocytes, and microvascular endothelial cells from an individual sample of human skin. The protocol describes step-by-step instructions for processing, cells isolation, and culture of neonatal foreskin, with adaptation for more demanding adult tissues. The availability of multiple isogenic cell types derived from individual skin samples offers the ability to investigate various areas of biology, in the context of cell-type specificity without potential confounding influence of inter-individual or genetic differences. For complete details on the use and execution of this protocol, please refer to Holliman et al. (2017), Horvath et al. (2019), Horvath et al. (2018), Kabacik et al. (2018), Lowe et al. (2020), Lu et al. (2019), and Lu et al. (2018).

Indexed as

Endothelial CellsSkinCell SeparationHumansInfant, NewbornKeratinocytesMelanocytesCell BiologyCell cultureCell isolationClinical ProtocolHealth Sciences

Identifiers

PMID35586317
PMCPMC9108981
OpenAlexW4229445464

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.