Evidence map›Paper›PMID 28729821›Full record

ArticleFrontiers in neuroscience2017

Optimized Model of Cerebral Ischemia

Oksana Rybachuk, Olga Kopach, Volodymyr Krotov, Nana Voitenko, Tatyana Pivneva

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Article
  2. Review
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  5. Review
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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.

Oksana RybachukDepartment of Sensory Signaling, Bogomoletz Institute of PhysiologyKyiv, Ukraine.
Olga KopachDepartment of Sensory Signaling, Bogomoletz Institute of PhysiologyKyiv, Ukraine.
Volodymyr KrotovDepartment of Sensory Signaling, Bogomoletz Institute of PhysiologyKyiv, Ukraine.
Nana VoitenkoDepartment of Sensory Signaling, Bogomoletz Institute of PhysiologyKyiv, Ukraine.
Tatyana PivnevaDepartment of Sensory Signaling, Bogomoletz Institute of PhysiologyKyiv, Ukraine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among all the brain, the hippocampus is the most susceptible region to ischemic lesion, with the highest vulnerability of CA1 pyramidal neurons to ischemic damage. This damage may cause either prompt neuronal death (within hours) or with a delayed appearance (over days), providing a window for applying potential therapies to reduce or prevent ischemic impairments. However, the time course when ischemic damage turns to neuronal death strictly depends on experimental modeling of cerebral ischemia and, up to now, studies were predominantly focused on a short time-window-from hours to up to a few days post-lesion. Using different schemes of oxygen-glucose deprivation (OGD), the conditions taking place upon cerebral ischemia, we optimized a model of mimicking ischemic conditions in organotypical hippocampal slices for the long-lasting assessment of CA1 neuronal death (at least 3 weeks). By combining morphology and electrophysiology, we show that prolonged (30-min duration) OGD results in a massive neuronal death and overwhelmed astrogliosis within a week post-OGD whereas OGD of a shorter duration (10-min) triggered programmed CA1 neuronal death with a significant delay-within 2 weeks-accompanied with drastically impaired CA1 neuron functions. Our results provide a rationale toward optimized modeling of cerebral ischemia for reliable examination of potential treatments for brain neuroprotection, neuro-regeneration, or testing neuroprotective compounds

Indexed as

cell deathneuronal excitabilityorganotypic hippocampal slice culturesoxygen-glucose deprivationsynaptic transmission

Identifiers

PMID28729821
PMCPMC5498507

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Registered trials

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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.