Evidence map›Paper›PMID 25925386›Full record

ReviewThe EMBO journal2015

Probing disorders of the nervous system using reprogramming approaches.

Justin K Ichida, Evangelos Kiskinis

Open access · hybridAbstract readReview
In one paragraph

Review in The EMBO journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

27 citing papers in PubMed, 53 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

2 authors at 2 institutions in 1 country.

Justin K IchidaDepartment of Stem Cells and Regenerative Medicine, Eli and Edythe Broad, CIRM Center for Regenerative Medicine and Stem Cell Research at USC, University of Southern California, Los Angeles, CA, USA ichida@usc.edu evangelos.kiskinis@northwestern.edu.
Evangelos KiskinisThe Ken and Ruth Davee Department of Neurology & Clinical Neurological Sciences and Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA ichida@usc.edu evangelos.kiskinis@northwestern.edu.
Northwestern University · USUniversity of Southern California · US

Funding

NINDS NIH HHS R00-NS07743
6 · The paper itself

Abstract

The groundbreaking technologies of induced pluripotency and lineage conversion have generated a genuine opportunity to address fundamental aspects of the diseases that affect the nervous system. These approaches have granted us unrestricted access to the brain and spinal cord of patients and have allowed for the study of disease in the context of human cells, expressing physiological levels of proteins and under each patient's unique genetic constellation. Along with this unprecedented opportunity have come significant challenges, particularly in relation to patient variability, experimental design and data interpretation. Nevertheless, significant progress has been achieved over the past few years both in our ability to create the various neural subtypes that comprise the nervous system and in our efforts to develop cellular models of disease that recapitulate clinical findings identified in patients. In this Review, we present tables listing the various human neural cell types that can be generated and the neurological disease modeling studies that have been reported, describe the current state of the field, highlight important breakthroughs and discuss the next steps and future challenges.

Indexed as

Cellular ReprogrammingModels, NeurologicalNervous System DiseasesNeuronsAnimalsHumansdirected differentiationdisease modelingneurologic disorderneuronal development

Identifiers

PMID25925386
PMCPMC4474524
OpenAlexW2085450663

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.