Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 176

The DOI matches its Crossref record.

Heritability of symptoms in an experimental model of neuropathic pain

Devor, M., Raber, P.·1990·Pain

Abstract

Male and female rats underwent transection and ligation of the sciatic and saphenous nerves, and the development of autonomy was monitored. The deafferented animals were then interbred, always selecting males and females that expressed relatively high and, alternatively, relatively low levels of autotomy. Offspring were similarly operated and interbred. By the sixth generation of selective breeding, lines were achieved in which autotomy was consistently high (HA) or consistently low (LA). There was no indication of sex linkage. Thermal and mechanical nocifensive responsiveness co-selected with propensity to express autotomy following nerve injury: response thresholds were lower in HA than in LA rats. F1 hybrids formed by crossing homozygous HA and LA animals showed low levels of autotomy, similar to LA stock. This indicates recessive inheritance of the autotomy trait. Backcrossing F1 hybrids onto the LA line yielded a low autotomy phenotype in almost all cases; backcrossing F1 hybrids onto HA stock yielded about 50% high autotomy and 50% low autotomy. These ratios are consistent with simple mendelian inheritance of a single gene. Taken together, the data suggest that autotomy is inherited as a single-gene autosomal recessive trait.

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 · 10.1016/0304-3959(90)91092-w

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 176

Metadata

Authors
Devor, M., & Raber, P.
Venue
Pain
Published
1990-07
Volume
42
Issue
1
Pages
51-67
ISSN
0304-3959 (ISSN-L)
OpenAlex
W2031447224
Cited by
176
References
0
FWCI
3.83
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: Heritability of symptoms in an experimental model of neuropathic pain. https://app.cochat.ai/papers/10.1016/0304-3959(90)91092-w
The paper
Devor, M., & Raber, P. (1990). Heritability of symptoms in an experimental model of neuropathic pain. Pain. https://doi.org/10.1016/0304-3959(90)91092-w

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.