Evidence map›Paper›PMID 39282386›Full record

ArticlebioRxiv : the preprint server for biology2024

An Efficient Direct Conversion Strategy to Generate Functional Astrocytes from Human Adult Fibroblasts.

Uchit Bhaskar, Emily Shrimpton, Jason Ayo, Asiya Prasla, Mark Z Kos, Melanie A Carless

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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
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.

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

6 authors.

Uchit BhaskarDepartment of Neuroscience, Developmental and Regenerative Biology, The University of Texas at San Antonio, Texas, United States 78249.ORCID 0000-0001-6523-4666
Emily ShrimptonDepartment of Neuroscience, Developmental and Regenerative Biology, The University of Texas at San Antonio, Texas, United States 78249.ORCID 0009-0003-3416-6260
Jason AyoDepartment of Neuroscience, Developmental and Regenerative Biology, The University of Texas at San Antonio, Texas, United States 78249.
Asiya PraslaDepartment of Neuroscience, Developmental and Regenerative Biology, The University of Texas at San Antonio, Texas, United States 78249.
Mark Z KosDivision of Human Genetics, South Texas Diabetes and Obesity Institute School of Medicine, University of Texas Rio Grande Valley, Texas, United States 78539.ORCID 0000-0003-3129-7057
Melanie A CarlessDepartment of Neuroscience, Developmental and Regenerative Biology, The University of Texas at San Antonio, Texas, United States 78249.

Funding

UTSA RISE Research Training ProgramR25GM060655 · NIGMS · UNIVERSITY OF TEXAS SAN ANTONIO · PI BAREA-RODRIGUEZ, EDWIN J · 2000 to 2022
$21.6M
DNA methylation signatures of Alzheimer's disease in aged astrocytesR21AG085428 · NIA · UNIVERSITY OF TEXAS SAN ANTONIO · PI CARLESS, MELANIE · 2023 to 2025
$459k
NIA NIH HHS R21 AG085428NIGMS NIH HHS R25 GM060655
6 · The paper itself

Abstract

Direct reprogramming approaches offer an attractive alternative to stem-cell-derived models, allowing the retention of epigenetic information and age-associated cellular phenotypes, and providing an expedited method to generate target cell types. Several groups have previously generated multiple neuronal subtypes, neural progenitor cells, oligodendrocytes, and other cell types directly from fibroblasts. However, while some groups have had success at the efficient conversion of

Indexed as

AstrocytesDirect conversionLineage reprogramming

Identifiers

PMID39282386
PMCPMC11398335

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.