Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 390

The DOI matches its Crossref record.

Human hair growth in vitro

Philpott, Michael P., Green, Martin R., Kealey, Terence·1990·Journal of Cell Science

Abstract

We report for the first time the successful maintenance and growth of human hair follicles in vitro. Human anagen hair follicles were isolated by microdissection from human scalp skin. Isolation of the hair follicles was achieved by cutting the follicle at the dermo-subcutaneous fat interface using a scalpel blade. Intact hair follicles were then removed from the fat using watchmakers’ forceps. Isolated hair follicles maintained free-floating in supplemented Williams E medium in individual wells of 24-well multiwell plates showed a significant increase in length over 4 days. The increase in length was seen to be attributed to the production of a keratinised hair shaft, and was not associated with the loss of hair follicle morphology. [methyl-3H]thymidine autoradiography confirmed that in vitro the in vivo pattern of DNA synthesis was maintained; furthermore, [35S]methionine labelling of keratins showed that their patterns of synthesis did not change with maintenance. The importance of this model to hair follicle biology is further demonstrated by the observations that TGF-βl has a negative growth-regulatory effect on hair follicles in vitro and that EGF mimics the in vivo depilatory effects that have been reported in sheep and mice.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1242/jcs.97.3.463

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 390

Metadata

Authors
Philpott, M. P., Green, M. R., & Kealey, T.
Venue
Journal of Cell Science
Published
1990-11-01
Volume
97
Issue
3
Pages
463-471
ISSN
  • 0021-9533 (ISSN-L)
  • 1477-9137
OpenAlex
W2343997548
Cited by
390
References
0
FWCI
22.61
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Human hair growth in vitro. https://app.cochat.ai/papers/10.1242/jcs.97.3.463
The paper
Philpott, M. P., Green, M. R., & Kealey, T. (1990). Human hair growth in vitro. Journal of Cell Science. https://doi.org/10.1242/jcs.97.3.463

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.