Evidence map›Paper›PMID 35507156›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Detection of Soluble and Insoluble Protein Species in Patient-Derived iPSCs.

Stephanie Santarriaga, Ian Luecke, Allison D Ebert

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
7.6field-weighted citation impact, top 3% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Stephanie SantarriagaDepartment of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA. ssantarriaga@mgh.harvard.edu.
Ian LueckeDepartment of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA.
Allison D EbertDepartment of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA. aebert@mcw.edu.
Medical College of Wisconsin · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein aggregation is one of the hallmarks of many neurodegenerative diseases. While protein aggregation is a heavily studied aspect of neurodegenerative disease, methods of detection vary from one model system to another. Induced pluripotent stem cells (iPSCs) present an opportunity to model disease using patient-specific cells. However, iPSC-derived neurons are fetal-like in maturity, making it a challenge to detect key features such as protein aggregation that are often exacerbated with age. Nevertheless, we have previously found abnormal soluble and insoluble protein burden in motor neurons generated from amyotrophic lateral sclerosis (ALS) iPSCs, though protein aggregation has not been readily detected in iPSC-derived neurons from other neurodegenerative diseases. Therefore, here we present an ultracentrifugation method that detects insoluble protein species in various models of neurodegenerative disease, including Huntington's disease, Alzheimer's disease, and ALS. This method is able to detect soluble, insoluble, and SDS-resistant species in iPSC-derived neurons and is designed to be flexible for optimal detection of various aggregation-prone proteins.

Indexed as

Amyotrophic Lateral SclerosisInduced Pluripotent Stem CellsNeurodegenerative DiseasesHumansMotor NeuronsProtein AggregatesProtein AggregatesAlzheimer’s DiseaseAmyotrophic Lateral SclerosisHuntington’s DiseaseInduced Pluripotent Stem CellsNeurodegenerationNeuronsProtein Aggregation

Identifiers

PMID35507156
OpenAlexW4285155912

What OpenQuestion 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 OpenQuestion graph.