Evidence map›Paper›PMID 26437460›Full record

ArticlePloS one2015

Predicting Neuroinflammation in Morphine Tolerance for Tolerance Therapy from Immunostaining Images of Rat Spinal Cord.

Shinn-Long Lin, Fang-Lin Chang, Shinn-Ying Ho, Phasit Charoenkwan, Kuan-Wei Wang, Hui-Ling Huang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 22% of its field
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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
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

6 authors at 3 institutions in 1 country.

Shinn-Long LinDepartment of Anesthesiology, Tri-Service General Hospital and National Defense Medical Center, Taipei, Taiwan.
Fang-Lin ChangDepartment of Anesthesiology, Kang-Ning General Hospital, Taipei, Taiwan.
Shinn-Ying HoInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan; Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan.
Phasit CharoenkwanInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan.
Kuan-Wei WangInstitute of Molecular Medicine and Bioengineering, National Chiao Tung University, Hsinchu, Taiwan.
Hui-Ling HuangInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan; Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan.
National Yang Ming Chiao Tung University · TWNational Defense Medical Center · TWUniversity of Kang Ning · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long-term morphine treatment leads to tolerance which attenuates analgesic effect and hampers clinical utilization. Recent studies have sought to reveal the mechanism of opioid receptors and neuroinflammation by observing morphological changes of cells in the rat spinal cord. This work proposes a high-content screening (HCS) based computational method, HCS-Morph, for predicting neuroinflammation in morphine tolerance to facilitate the development of tolerance therapy using immunostaining images for astrocytes, microglia, and neurons in the spinal cord. HCS-Morph first extracts numerous HCS-based features of cellular phenotypes. Next, an inheritable bi-objective genetic algorithm is used to identify a minimal set of features by maximizing the prediction accuracy of neuroinflammation. Finally, a mathematic model using a support vector machine with the identified features is established to predict drug-treated images to assess the effects of tolerance therapy. The dataset consists of 15 saline controls (1 μl/h), 15 morphine-tolerant rats (15 μg/h), and 10 rats receiving a co-infusion of morphine (15 μg/h) and gabapentin (15 μg/h, Sigma). The three individual models of astrocytes, microglia, and neurons for predicting neuroinflammation yielded respective Jackknife test accuracies of 96.67%, 90.00%, and 86.67% on the 30 rats, and respective independent test accuracies of 100%, 90%, and 60% on the 10 co-infused rats. The experimental results suggest that neuroinflammation activity expresses more predominantly in astrocytes and microglia than in neuron cells. The set of features for predicting neuroinflammation from images of astrocytes comprises mean cell intensity, total cell area, and second-order geometric moment (relating to cell distribution), relevant to cell communication, cell extension, and cell migration, respectively. The present investigation provides the first evidence for the role of gabapentin in the attenuation of morphine tolerance from phenotypic changes of astrocytes and microglia. Based on neuroinflammation prediction, the proposed computer-aided image diagnosis system can greatly facilitate the development of tolerance therapy with anti-inflammatory drugs.

Indexed as

AminesAnalgesics, OpioidAnimalsAstrocytesCyclohexanecarboxylic AcidsDrug ToleranceGabapentingamma-Aminobutyric AcidImmunohistochemistryMaleMicrogliaMorphineNeuronsPain MeasurementRatsRats, WistarAminesAnalgesics, OpioidCyclohexanecarboxylic AcidsGabapentingamma-Aminobutyric AcidMorphine

Identifiers

PMID26437460
PMCPMC4593634
OpenAlexW2219570324

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.