Evidence map›Paper›PMID 33597593›Full record

ArticleScientific reports2021

Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration.

Ruyi Huang, Ali A Nikooyan, Bo Xu, M Selvan Joseph, Hamidreza Ghasemi Damavandi, Nathan von Trotha, Lilian Li, Ashok Bhattarai, Deeba Zadeh, Yeji Seo and 5 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

15 authors at 8 institutions in 1 country.

Ruyi Huang *Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Ste. 536, Los Angeles, CA, 90095-6901, USA.
Ali A Nikooyan *Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Ste. 536, Los Angeles, CA, 90095-6901, USA.
Bo XuDepartment of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Ste. 536, Los Angeles, CA, 90095-6901, USA.
M Selvan JosephDepartment of Kinesiology, Nutritional and Food Sciences, California State University, Los Angeles, Los Angeles, CA, 90032, USA.
Hamidreza Ghasemi DamavandiOffice of Knowledge Enterprise Development, Arizona State University, Tempe, AZ, 85281, USA.
Nathan von TrothaDepartment of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Ste. 536, Los Angeles, CA, 90095-6901, USA.
Lilian LiCollege of Osteopathic Medicine, Touro University Nevada, Henderson, NV, 89014, USA.
Ashok BhattaraiThe Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA.
Deeba ZadehDepartment of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Ste. 536, Los Angeles, CA, 90095-6901, USA.
Yeji SeoDepartment of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Ste. 536, Los Angeles, CA, 90095-6901, USA.
Xingquan LiuDepartment of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Ste. 536, Los Angeles, CA, 90095-6901, USA.
Patrick A TruongDepartment of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Ste. 536, Los Angeles, CA, 90095-6901, USA.
Edward H KooDepartment of Neuroscience, San Diego School of Medicine, University of California, San Diego, La Jolla, CA, 92093, USA.
J C LeiterDepartment of Molecular and Systems Biology, Geisel School of Medicine of Dartmouth College, Lebanon, NH, 03756, USA.
Daniel C LuDepartment of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Ste. 536, Los Angeles, CA, 90095-6901, USA. dclu@mednet.ucla.edu.
University of California, Los Angeles · USArizona State University · USCalifornia State University Los Angeles · USDartmouth College · USThe Ohio State University Wexner Medical Center · USTouro University Nevada · USUniversity of California, Berkeley · USUniversity of California, San Diego · US

Funding

Stimulation of novel spinal respiratory circuit to restore breathing in ventilator-dependent patients with SCI.UH3NS119772 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Daniel Lu · 2021 to 2026
$4.9M
Characterization of Novel Neural Respiratory Circuit to Counter Opioid-Induced Respiratory DepressionR01DA047637 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LU, DANIEL · 2020 to 2024
$3.5M
NIDA NIH HHS R01 DA047637NINDS NIH HHS UH3 NS119772
6 · The paper itself

Abstract

Motor deficits are observed in Alzheimer's disease (AD) prior to the appearance of cognitive symptoms. To investigate the role of amyloid proteins in gait disturbances, we characterized locomotion in APP-overexpressing transgenic J20 mice. We used three-dimensional motion capture to characterize quadrupedal locomotion on a treadmill in J20 and wild-type mice. Sixteen J20 mice and fifteen wild-type mice were studied at two ages (4- and 13-month). A random forest (RF) classification algorithm discriminated between the genotypes within each age group using a leave-one-out cross-validation. The balanced accuracy of the RF classification was 92.3 ± 5.2% and 93.3 ± 4.5% as well as False Negative Rate (FNR) of 0.0 ± 0.0% and 0.0 ± 0.0% for the 4-month and 13-month groups, respectively. Feature ranking algorithms identified kinematic features that when considered simultaneously, achieved high genotype classification accuracy. The identified features demonstrated an age-specific kinematic profile of the impact of APP-overexpression. Trunk tilt and unstable hip movement patterns were important in classifying the 4-month J20 mice, whereas patterns of shoulder and iliac crest movement were critical for classifying 13-month J20 mice. Examining multiple kinematic features of gait simultaneously could also be developed to classify motor disorders in humans.

Indexed as

Alzheimer DiseaseAmyloid beta-PeptidesAmyloid beta-Protein PrecursorAnimalsBiomechanical PhenomenaDisease Models, AnimalGaitHumansMachine LearningMiceMice, Inbred C57BLMice, TransgenicNeurodegenerative DiseasesPlaque, AmyloidAmyloid beta-PeptidesAmyloid beta-Protein Precursor

Identifiers

PMID33597593
PMCPMC7889656
OpenAlexW3132700032

What OpenQuestion 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 OpenQuestion graph.