Evidence map›Paper›PMID 30521828›Full record

ArticleJournal of neuroscience methods2019

A new automated device for quantifying mechanical nociceptive responses.

Jahrane Dale, Haocheng Zhou, Qiaosheng Zhang, Amrita Singh, Jing Wang

Abstract read
In one paragraph

Article in Journal of neuroscience methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Jahrane DaleDepartment of Anesthesiology, Perioperative Care and Pain Medicine, New York University School of Medicine, New York, NY, USA.
Haocheng ZhouDepartment of Anesthesiology, Perioperative Care and Pain Medicine, New York University School of Medicine, New York, NY, USA; Department of Pain Medicine, The Third Xiangya Hospital and Institute of Pain Medicine, Central South University, Changsha, Hunan Province, China.
Qiaosheng ZhangDepartment of Anesthesiology, Perioperative Care and Pain Medicine, New York University School of Medicine, New York, NY, USA.
Amrita SinghDepartment of Anesthesiology, Perioperative Care and Pain Medicine, New York University School of Medicine, New York, NY, USA.
Jing WangDepartment of Anesthesiology, Perioperative Care and Pain Medicine, New York University School of Medicine, New York, NY, USA; Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA. Electronic address: jing.wang2@nyumc.org.

Funding

Central glutamate signaling in postoperative pain regulation - Revision - 1R01GM115384 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Jing Wang · 2015 to 2026
$5.4M
Neocortical Control of the ThalamusR01NS100016 · NINDS · BROWN UNIVERSITY · PI CONNORS, BARRY W, CRUIKSHANK, SCOTT J · 2017 to 2021
$3.0M
CRCN: Dissecting Neural Circuits for Acute PainR01NS100065 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CHEN, ZHE SAGE, WANG, JING · 2016 to 2019
$1.5M
NIGMS NIH HHS R01 GM115384NINDS NIH HHS R01 NS100016NINDS NIH HHS R01 NS100065
6 · The paper itself

Abstract

backgroundTraditional methods to assess pain in rodents depend on measures of nociceptive responses, most commonly from the hind paws. While these measures can quantify nociceptive responses to allow pharmacologic testing, they typically have high inter-experimenter variability and are not time-sensitive enough to correct with neural processes that occur on millisecond scales. NEW

methodWe have invented a pain detection device that uses changes in skin conductance to measure nocifensive withdrawal responses. This device automatically records how long it takes for a rodent to withdraw its paw from the onset of peripheral noxious stimulation.

resultsWith this pain device, we can record accurate timing (on the millisecond scale) for nociceptive responses, with high accuracy and consistency. Furthermore, we demonstrate that this device can allow us to distinguish the nociceptive response to mechanical noxious stimuli of different intensities. Finally, we demonstrate that this device can be digitally integrated to correlate behavior with neural activities in real-time.

conclusionsThis study demonstrates a new automated, temporally specific method for quantifying nociceptive responses to facilitate pain studies.

Indexed as

AnimalsGalvanic Skin ResponseInflammationMaleNociceptionPainPain MeasurementRats, Sprague-DawleySomatosensory CortexAutomatedNociceptivePainTouch circuitWithdrawal

Identifiers

PMID30521828
PMCPMC6349465

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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.