Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 245

The DOI matches its Crossref record.

CHEMICAL METHOD FOR THE DETERMINATION OF 17-HYDROXYCORTICOSTEROIDS AND 17-KETOSTEROIDS IN URINE FOLLOWING HYDROLYSIS WITH β-GLUCURONIDASE*

GLENN, E. MYLES, NELSON, DON H.·1953·The Journal of Clinical Endocrinology & Metabolism

Abstract

METHODS for the estimation of metabolites of the adrenocortical steroids thus far published have given only partially satisfactory estimates of adrenocortical function. A method has been developed which gives reproducible determinations of 17,21-dihydroxy-20-ketones and 17-ketosteroids present in urine, either in the free form or conjugated as glucuronides. The acid hydrolysis of urinary adrenal steroid metabolites has been accomplished with varying degrees of success by a number of investigators (1–4), but there is considerable evidence suggesting loss or alteration of steroids during the hydrolytic process (5, 6). It has been shown that a large part of the adrenocortical steroids in urine are conjugated as glucuronides (7–10). In the present method hydrolysis with β-glucuronidase was employed and consistent levels of adrenocortical steroid metabolites were found after chromatography on a Florisil column.

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 · 10.1210/jcem-13-8-911

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 245

Metadata

Authors
GLENN, E. M., & NELSON, D. H.
Venue
The Journal of Clinical Endocrinology & Metabolism
Published
1953-08
Volume
13
Issue
8
Pages
911-921
ISSN
  • 0021-972X (ISSN-L)
  • 1945-7197
OpenAlex
W2082370852
Cited by
245
References
0
FWCI
14.42
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: CHEMICAL METHOD FOR THE DETERMINATION OF 17-HYDROXYCORTICOSTEROIDS AND 17-KETOSTEROIDS IN URINE FOLLOWING HYDROLYSIS WITH β-GLUCURONIDASE*. https://app.cochat.ai/papers/10.1210/jcem-13-8-911
The paper
GLENN, E. M., & NELSON, D. H. (1953). CHEMICAL METHOD FOR THE DETERMINATION OF 17-HYDROXYCORTICOSTEROIDS AND 17-KETOSTEROIDS IN URINE FOLLOWING HYDROLYSIS WITH β-GLUCURONIDASE*. The Journal of Clinical Endocrinology & Metabolism. https://doi.org/10.1210/jcem-13-8-911

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.