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Cited by 392

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Pituitary Extracts and Steroid Hormones in the Control of 3T3 Cell Growth

Open access
Armelin, Hugo A.·1973·Proceedings of the National Academy of Sciences

Abstract

Results are reported showing that pituitary extracts stimulate growth of 3T3 cells, an established line of mouse fibroblast. Cells were cultured in medium containing an organic buffer (HEPES; N -2-hydroxyethylpiperazine- N ′-2-ethanesulfonic acid), which increases the serum requirement for cell growth. The pituitary growth-prompting activity is ( a ) not dialyzable; ( b ) thermolabile; ( c ) protease sensitive; and ( d ) enhanced by hydrocortisone (a steroid hormone). Activity was quantitatively assayed by measurement of stimulation of cell division or [ 3 H]thymidine uptake into DNA. The active species is probably different from pituitary protein hormones and it seems to be effective at concentrations observed for protein hormones in vivo . 3T3 cells transformed by simian virus 40 are not responsive to this activity.

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Crossref · 10.1073/pnas.70.9.2702

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Metadata

Authors
Armelin, H. A.
Venue
Proceedings of the National Academy of Sciences
Published
1973-09
Volume
70
Issue
9
Pages
2702-2706
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1988188677
Cited by
392
References
1
FWCI
19.19
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Pituitary Extracts and Steroid Hormones in the Control of 3T3 Cell Growth. https://app.cochat.ai/papers/10.1073/pnas.70.9.2702
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Armelin, H. A. (1973). Pituitary Extracts and Steroid Hormones in the Control of 3T3 Cell Growth. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.70.9.2702

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.