Evidence map›Paper›PMID 34033080›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2021

Slice Culture Modeling of CNS Viral Infection.

Kalen R Dionne, Kenneth L Tyler, Penny Clarke

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Kalen R DionneDepartment of Neurology, Denver Veterans Affairs Medical Center, Aurora, CO, USA.
Kenneth L TylerDepartment of Neurology, Denver Veterans Affairs Medical Center, Aurora, CO, USA.
Penny ClarkeDepartment of Neurology, Denver Veterans Affairs Medical Center, Aurora, CO, USA. Ken.Tyler@ucdenver.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The complexity of the central nervous system (CNS) is not recapitulated in cell culture models. Thin slicing and subsequent culture of CNS tissue has become a valued means to study neuronal and glial biology within the context of the physiologically relevant tissue milieu. Modern membrane-interface slice culturing methodology allows for straightforward access to both CNS tissue and feeding medium, enabling experimental manipulations and analyses that would otherwise be impossible in vivo. CNS slices can be successfully maintained in culture for up to several weeks for investigation of evolving pathology and long-term intervention in models of chronic neurologic disease.Herein, membrane-interface slice culture models for studying viral encephalitis and myelitis are detailed, with emphasis on the use of these models for investigation of pathogenesis and evaluation of novel treatment strategies. We describe techniques to (1) generate brain and spinal cord slices from rodent donors, (2) virally infect slices, (3) monitor viral replication, (4) assess virally induced injury/apoptosis, (5) characterize "CNS-specific" cytokine production, and, (6) treat slices with cytokines/pharmaceuticals. Although our focus is on CNS viral infection, we anticipate that the described methods can be adapted to address a wide range of investigations within the fields of neuropathology, neuroimmunology, and neuropharmacology.

Indexed as

AnimalsAnimals, NewbornAntiviral AgentsApoptosisBrainCytokinesEncephalitis, ViralHost-Pathogen InteractionsInflammation MediatorsMiceMyelitisSpinal CordTissue Culture TechniquesVirus ReplicationAntiviral AgentsCytokinesInflammation MediatorsApoptosisBrain sliceCaspaseCytokineEncephalitisEx vivoMyelitisOrganotypicSpinal cord sliceVirus

Identifiers

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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.