Evidence map›Paper›PMID 29490258›Full record

ArticleBiophysical journal2018

Deciphering the Dynamical Origin of Mixed Population during Neural Stem Cell Development.

Dola Sengupta, Sandip Kar

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2018. 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
0.4field-weighted citation impact, top 41% 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

1 citing paper in PubMed, 8 citations in OpenAlex.

  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

2 authors at 1 institution in 1 country.

Dola SenguptaDepartment of Chemistry, IIT Bombay, Powai, Mumbai, India.
Sandip KarDepartment of Chemistry, IIT Bombay, Powai, Mumbai, India. Electronic address: sandipkar@iitb.ac.in.
Indian Institute of Technology Bombay · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neural stem cells (NSCs) often give rise to a mixed population of cells during differentiation. However, the dynamical origin of these mixed states is poorly understood. In this article, our mathematical modeling study demonstrates that the bone morphogenetic protein 2 (BMP2) mediated disparate differentiation dynamics of NSCs in central and peripheral nervous systems essentially function through two distinct bistable switches that are mutually interconnected via a mushroom-like bifurcation. Stochastic simulations of the model reveal that the mixed population originates due to the existence of these bistable switching regulations and that the maintenance of such mixed states depends on the level of stochastic fluctuations of the system. It further demonstrates that due to extrinsic variability, cells in an NSC population can dynamically transit from mushroom to a unique isola kind of bifurcation state, which essentially extends the range of the BMP2-driven mixed population state during differentiation. Importantly, the model predicts that by individually altering the expression level of key regulatory proteins, the NSCs can be converted entirely to a preferred phenotype for BMP2 doses that previously resulted in a mixed population. Our findings show that efficient neuronal regeneration can be achieved by systematically maneuvering the differentiation dynamics.

Indexed as

Models, TheoreticalBone Morphogenetic Protein 2Cell DifferentiationCentral Nervous SystemComputer SimulationGene Expression Regulation, DevelopmentalHumansNeural Stem CellsNeurogenesisPeripheral Nervous SystemStochastic ProcessesTranscription Factor 3BMP2 protein, humanBone Morphogenetic Protein 2Transcription Factor 3

Identifiers

PMID29490258
PMCPMC5985008
OpenAlexW2788686648

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.