Cardiac neural crest (CNC) cells are pluripotent cells derived from the dorsal neural tube that migrate and contribute to the remodeling of pharyngeal arch arteries and septation of the cardiac outflow tract (OFT). Numerous molecular cascades regulate the induction, specification, delamination, and migration of the CNC. Extensive analyses of the CNC ranging from chick ablation models to molecular biology studies have explored the mechanisms of heart development and disease, particularly involving the OFT and aortic arch (AA) system. Recent studies focus more on reciprocal signaling between the CNC and cells originated from the second heart field (SHF), which are essential for the development of the OFT myocardium, providing new insights into the molecular mechanisms underlying congenital heart diseases (CHDs) and some human syndromes.
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http://dx.doi.org/10.1101/cshperspect.a036715 | DOI Listing |
Comput Biol Med
January 2025
Institute of Biomedical Engineering, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Fetal echocardiography (ultrasound of the fetal heart) plays a vital role in identifying heart defects, allowing clinicians to establish prenatal and postnatal management plans. Machine learning-based methods are emerging to support the automation of fetal echocardiographic analysis; this review presents the findings from a literature review in this area. Searches were queried at leading indexing platforms ACM, IEEE Xplore, PubMed, Scopus, and Web of Science, including papers published until July 2023.
View Article and Find Full Text PDFNeural Netw
January 2025
Tsinghua University, Beijing, China. Electronic address:
Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse wave, heart rate and respiration rate with better accuracy. However, most existing ANN-based methods require substantial computing resources, which poses challenges for effective deployment on mobile devices. Spiking neural networks (SNNs), on the other hand, hold immense potential for energy-efficient deep learning owing to their binary and event-driven architecture.
View Article and Find Full Text PDFKidney Res Clin Pract
January 2025
Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Background: Acute kidney injury (AKI) is a critical clinical condition that requires immediate intervention. We developed an artificial intelligence (AI) model called PRIME Solution to predict AKI and evaluated its ability to enhance clinicians' predictions.
Methods: The PRIME Solution was developed using convolutional neural networks with residual blocks on 183,221 inpatient admissions from a tertiary hospital (2013-2017) and externally validated with 4,501 admissions at another tertiary hospital (2020-2021).
J Transl Med
January 2025
Department of Anatomy & Embryology, Leiden University Medical Center, P.O. Box 9600, Postal Zone: S-1-P, 2300 RC, Leiden, The Netherlands.
Background: Prenatal development of autonomic innervation of sinus venosus-related structures might be related to atrial arrhythmias later in life. Most of the pioneering studies providing embryological background are conducted in animal models. To date, a detailed comparison with the human cardiac autonomic nervous system (cANS) is lacking.
View Article and Find Full Text PDFInt J Biol Macromol
January 2025
Polymers and Pigments Department, Chemical Industries Research Institute, National Research Centre, Dokki, Giza 12622, Egypt.
Integrating nanotechnology with tissue engineering has revolutionized biomedical sciences, enabling the development of advanced therapeutic strategies. Tissue engineering applications widely utilize alginate due to its biocompatibility, mild gelation conditions, and ease of modification. Combining different nanomaterials with alginate matrices enhances the resulting nanocomposites' physicochemical properties, such as mechanical, electrical, and biological properties, as well as their surface area-to-volume ratio, offering significant potential for tissue engineering applications.
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