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Retinoic acid drives surface epithelium fate determination through the TCF7-MSX2 axis.
Cell Mol Life Sci
December 2024
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
Understanding how embryonic progenitors decode extrinsic signals and transform into lineage-specific regulatory networks to drive cell fate specification is a fundamental, yet challenging question. Here, we develop a new model of surface epithelium (SE) differentiation induced by human embryonic stem cells (hESCs) using retinoic acid (RA), and identify BMP4 as an essential downstream signal in this process. We show that the retinoid X receptors, RXRA and RXRB, orchestrate SE commitment by shaping lineage-specific epigenetic and transcriptomic landscapes.
View Article and Find Full Text PDFReading the repertoire: Progress in adaptive immune receptor analysis using machine learning.
Cell Syst
December 2024
Imprint Labs, LLC, New York, NY, USA; Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway. Electronic address:
The adaptive immune system holds invaluable information on past and present immune responses in the form of B and T cell receptor sequences, but we are limited in our ability to decode this information. Machine learning approaches are under active investigation for a range of tasks relevant to understanding and manipulating the adaptive immune receptor repertoire, including matching receptors to the antigens they bind, generating antibodies or T cell receptors for use as therapeutics, and diagnosing disease based on patient repertoires. Progress on these tasks has the potential to substantially improve the development of vaccines, therapeutics, and diagnostics, as well as advance our understanding of fundamental immunological principles.
View Article and Find Full Text PDFColonNeXt: Fully Convolutional Attention for Polyp Segmentation.
J Imaging Inform Med
December 2024
Hong Duc University, 565 Quang Trung, Dong Ve Ward, Thanh Hoa, 40000, Thanh Hoa, Viet Nam.
This study introduces ColonNeXt, a novel fully convolutional attention-based model for polyp segmentation from colonoscopy images, aimed at the enhancing early detection of colorectal cancer. Utilizing a purely convolutional neural network (CNN), ColonNeXt integrates an encoder-decoder structure with a hierarchical multi-scale context-aware network (MSCAN) in the encoder and a convolutional block attention module (CBAM) in the decoder. The decoder further includes a proposed CNN-based feature attention mechanism for selective feature enhancement, ensuring precise segmentation.
View Article and Find Full Text PDFA variety of early literacy assessments are available to monitor student response to instruction in early reading skills. The purpose of this study was to explore the degree to which growth during the second half of kindergarten on measures of alphabetic principle (i.e.
View Article and Find Full Text PDFDecoding AI ethics from Users' lens in education: A systematic review.
Heliyon
October 2024
Faculty of Applied Sciences, Macao Polytechnic University, Macao, China.
In recent years, Artificial Intelligence (AI) has witnessed remarkable expansion, greatly benefiting the education sector. Nonetheless, this advancement brings forth several ethical dilemmas. The existing research on these ethical concerns within the educational framework is notably scarce, particularly when viewed from a user's standpoint.
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