Evidence map›Paper›PMID 29204344›Full record

ArticleNeuroImage. Clinical2018

MR brain volumetric measurements are predictive of neurobehavioral impairment in the HIV-1 transgenic rat.

Rafael Casas, Siva Muthusamy, Paul G Wakim, Sanhita Sinharay, Margaret R Lentz, William C Reid, Dima A Hammoud

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

11 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Dopamine, Immunity, and Disease.Pharmacological reviews · 2023
    Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
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

7 authors at 1 institution in 1 country.

Rafael CasasCenter for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.
Siva MuthusamyCenter for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.
Paul G WakimBiostatistics and Clinical Epidemiology Service, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.
Sanhita SinharayCenter for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.
Margaret R LentzCenter for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.
William C ReidCenter for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.
Dima A HammoudCenter for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States. Electronic address: hammoudd@cc.nih.gov.
National Institutes of Health Clinical Center · US

Funding

Molecular Imaging of neuroHIv using animals models of diseaseZIACL090037 · CLC · CLINICAL CENTER · PI HAMMOUD, DIMA A · 2016 to 2019
$0k
6 · The paper itself

Abstract

introductionHIV infection is known to be associated with brain volume loss, even in optimally treated patients. In this study, we assessed whether dynamic brain volume changes over time are predictive of neurobehavorial performance in the HIV-1 transgenic (Tg) rat, a model of treated HIV-positive patients. MATERIALS AND

methodsCross-sectional brain MRI imaging was first performed comparing Tg and wild type (WT) rats at 3 and 19 months of age. Longitudinal MRI and neurobehavioral testing of another group of Tg and WT rats was then performed from 5 to 23 weeks of age. Whole brain and subregional image segmentation was used to assess the rate of brain growth over time. We used repeated-measures mixed models to assess differences in brain volumes and to establish how predictive the volume differences are of specific neurobehavioral deficits.

resultsCross-sectional imaging showed smaller whole brain volumes in Tg compared to WT rats at 3 and at 19 months of age. Longitudinally, Tg brain volumes were smaller than age-matched WT rats at all time points, starting as early as 5 weeks of age. The Tg striatal growth rate delay between 5 and 9 weeks of age was greater than that of the whole brain. Striatal volume in combination with genotype was the most predictive of rota-rod scores and in combination with genotype and age was the most predictive of total exploratory activity scores in the Tg rats.

conclusionThe disproportionately delayed striatal growth compared to whole brain between 5 and 9 weeks of age and the role of striatal volume in predicting neurobehavioral deficits suggest an important role of the dopaminergic system in HIV associated neuropathology. This might explain problems with motor coordination and executive decisions in this animal model. Smaller brain and subregional volumes and neurobehavioral deficits were seen as early as 5 weeks of age, suggesting an early brain insult in the Tg rat. Neuroprotective therapy testing in this model should thus target this early stage of development, before brain damage becomes irreversible.

Indexed as

AnimalsBehavior, AnimalBrainHIV-1HIV InfectionsMagnetic Resonance ImagingMaleMental DisordersRatsRats, TransgenicBrain volumeHIV-1 transgenic ratMRINeurobehavioral testing

Identifiers

PMID29204344
PMCPMC5705794
OpenAlexW2770886391

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.