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Cells
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Pluripotent Stem Cells: Current Applications and Future Directions
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Pluripotent Stem Cells: Current Applications and Future Directions

A special issue of Cells (ISSN 2073-4409). This special issue belongs to the section "Stem Cells".

Deadline for manuscript submissions: 30 August 2024 | Viewed by 927

Special Issue Editor

Dr. Julie Bejoy

E-Mail Website
Guest Editor
Vanderbilt University Medical Center, Nashville, TN, USA
Interests: stem cells; brain organoids; kidney organoids; stem cell extracellular vesicles; tissue regeneration; disease modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pluripotent stem cells (PSCs) are one of the most versatile stem cells that can differentiate into multiple cell types. PSCs, including both embryonic stem cells and induced pluripotent stem cells, have been differentiated into all three germ layers: ectoderm, mesoderm, and endoderm. PSCs can be used to derive three-dimensional models of organs called organoids, which can replicate the architecture and function of the organs. Compared to the traditional cell culture approach, these organoids provide a more physiologically relevant platform, allowing researchers to study complex diseases as well as screen drugs. PSCs have contributed significantly in advancing tissue engineering with the future possibilities of personalized medicine. This Special Issue will feature articles providing insights into the ongoing research showcasing the pluripotent stem cells’ potential in diverse therapeutic applications across various fields.

Dr. Julie Bejoy
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cells is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • induced pluripotent stem cells
  • organoids
  • reprogramming
  • differentiation
  • spheroids
  • cortical organoids
  • intestinal organoids
  • kidney organoids
  • cardiomyocytes
  • astrocytes
  • microglia
  • personalized medicine
  • drug screening
  • disease modeling

Published Papers (1 paper)

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Research

14 pages, 15582 KiB  
Article
Deep Learning Powered Identification of Differentiated Early Mesoderm Cells from Pluripotent Stem Cells
by Sakib Mohammad, Arpan Roy, Andreas Karatzas, Sydney L. Sarver, Iraklis Anagnostopoulos and Farhan Chowdhury
Cells 2024, 13(6), 534; https://doi.org/10.3390/cells13060534 - 18 Mar 2024
Viewed by 769
Abstract
Pluripotent stem cells can be differentiated into all three germ-layers including ecto-, endo-, and mesoderm in vitro. However, the early identification and rapid characterization of each germ-layer in response to chemical and physical induction of differentiation is limited. This is a long-standing issue [...] Read more.
Pluripotent stem cells can be differentiated into all three germ-layers including ecto-, endo-, and mesoderm in vitro. However, the early identification and rapid characterization of each germ-layer in response to chemical and physical induction of differentiation is limited. This is a long-standing issue for rapid and high-throughput screening to determine lineage specification efficiency. Here, we present deep learning (DL) methodologies for predicting and classifying early mesoderm cells differentiated from embryoid bodies (EBs) based on cellular and nuclear morphologies. Using a transgenic murine embryonic stem cell (mESC) line, namely OGTR1, we validated the upregulation of mesodermal genes (Brachyury (T): DsRed) in cells derived from EBs for the deep learning model training. Cells were classified into mesodermal and non-mesodermal (representing endo- and ectoderm) classes using a convolutional neural network (CNN) model called InceptionV3 which achieved a very high classification accuracy of 97% for phase images and 90% for nuclei images. In addition, we also performed image segmentation using an Attention U-Net CNN and obtained a mean intersection over union of 61% and 69% for phase-contrast and nuclear images, respectively. This work highlights the potential of integrating cell culture, imaging technologies, and deep learning methodologies in identifying lineage specification, thus contributing to the advancements in regenerative medicine. Collectively, our trained deep learning models can predict the mesoderm cells with high accuracy based on cellular and nuclear morphologies. Full article
(This article belongs to the Special Issue Pluripotent Stem Cells: Current Applications and Future Directions)
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