Evidence map›Paper›PMID 38954533›Full record

ArticleGenetics and molecular biology2024

Exploring mood disorders and treatment options using human stem cells.

Autumn Hudock, Zaira Paulina Leal, Amandeep Sharma, Arianna Mei, Renata Santos, Maria Carolina Marchetto

Abstract read
In one paragraph

Article in Genetics and molecular biology, 2024. 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
–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

1 citing paper in PubMed.

  1. Review
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.

Autumn HudockUniversity of California San Diego, Department of Anthropology, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-4722-754X
Zaira Paulina LealUniversity of California San Diego, Department of Anthropology, La Jolla, CA, USA.ORCID http://orcid.org/0009-0002-2902-9248
Amandeep SharmaThe Salk Institute for Biological Studies, Laboratory of Genetics, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-2091-9618
Arianna MeiThe Salk Institute for Biological Studies, Laboratory of Genetics, La Jolla, CA, USA.
Renata SantosThe Salk Institute for Biological Studies, Laboratory of Genetics, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-3085-5128
Maria Carolina MarchettoUniversity of California San Diego, Department of Anthropology, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-0449-9051

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite their global prevalence, the mechanisms for mood disorders like bipolar disorder and major depressive disorder remain largely misunderstood. Mood stabilizers and antidepressants, although useful and effective for some, do not have a high responsiveness rate across those with these conditions. One reason for low responsiveness to these drugs is patient heterogeneity, meaning there is diversity in patient characteristics relating to genetics, etiology, and environment affecting treatment. In the past two decades, novel induced pluripotent stem cell (iPSC) research and technology have enabled the use of human-derived brain cells as a new model to study human disease that can help account for patient variance. Human iPSC technology is an emerging tool to better understand the molecular mechanisms of these disorders as well as a platform to test novel treatments and existing pharmaceuticals. This literature review describes the use of iPSC technology to model bipolar and major depressive disorder, common medications used to treat these disorders, and novel patient-derived alternative treatment methods for non-responders stemming from past publications, as well as presenting new data derived from these models.

Identifiers

PMID38954533
PMCPMC11223183

What OpenQuestion holds

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Registered trials

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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.