Evidence map›Paper›PMID 37423987›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Culture of Three-Dimensional Madin-Darby Canine Kidney (MDCK) Cysts for In Vitro Drug Testing in Polycystic Kidney Disease.

Sayanthooran Saravanabavan, Gopala K Rangan

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 76% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 2 institutions in 1 country.

Sayanthooran SaravanabavanMichael Stern Laboratory for Polycystic Kidney Disease, Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, Australia.
Gopala K RanganMichael Stern Laboratory for Polycystic Kidney Disease, Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, Australia. g.rangan@sydney.edu.au.
The University of Sydney · AUWestmead Institute for Medical Research · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The formation and growth of kidney cysts (fluid-filled structures lined by epithelial cells) is the primary pathological abnormality in polycystic kidney disease (PKD). Multiple molecular pathways are disrupted in kidney epithelial precursor cells, which lead to altered planar cell polarity, increased proliferation, and fluid secretion, which together with extracellular matrix remodelling culminates in the formation and growth of cysts. Three-dimensional (3D) in vitro cyst models serve as suitable preclinical models to screen candidate drugs for PKD. Madin-Darby Canine Kidney (MDCK) epithelial cells form polarized monolayers with a fluid-filled lumen when suspended in a collagen gel, and their growth is accelerated with the addition of forskolin, a cyclic adenosine monophosphate (cAMP) agonist. Candidate drugs for PKD can be screened for their ability to modulate growth of forskolin-treated MDCK cysts by measuring and quantifying cyst images acquired at progressive timepoints. In this chapter, we describe the detailed methods for the culture and growth of MDCK cysts in a collagen matrix and a protocol for their use in testing candidate drugs to prevent cyst formation and growth.

Indexed as

CystsPolycystic Kidney DiseasesAnimalsColforsinCollagenDogsKidneyMadin Darby Canine Kidney CellsColforsinCollagenCollagen matrixCyst growthDrug screeningIn vitro cystsPKDPreclinical model

Identifiers

PMID37423987
OpenAlexW4383709846

What Socratic holds

Textmetadata
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.