An Improved Nested U-Net Network for Fluorescence In Situ Hybridization Cell Image Segmentation.

Fluorescence in situ hybridization (FISH) is a powerful cytogenetic method used to precisely detect and localize nucleic acid sequences. This technique is proving to be an invaluable tool in medical diagnostics and has made significant contributions to biology and the life sciences. However, the number of cells is large and the nucleic acid sequences are disorganized in the FISH images taken using the microscope. Processing and analyzing images is a time-consuming and laborious task for researchers, as it can easily tire the human eyes and lead to errors in judgment. In recent years, deep learning has made significant progress in the field of medical imaging, especially the successful application of introducing the attention mechanism. The attention mechanism, as a key component of deep learning, improves the understanding and interpretation of medical images by giving different weights to different regions of the image, enabling the model to focus more on important features. To address the challenges in FISH image analysis, we combined medical imaging with deep learning to develop the SEAM-Unet++ automated cell contour segmentation algorithm with integrated attention mechanism. The significant advantage of this algorithm is that it improves the accuracy of cell contours in FISH images. Experiments have demonstrated that by introducing the attention mechanism, our method is able to segment cells that are adherent to each other more efficiently.

p57 Suppresses the Pluripotency and Proliferation of Mouse Embryonic Stem Cells by Positively Regulating p53 Activation.

Embryonic stem cells (ESCs) are pluripotent stem cells that have indefinite self-renewal capacities under appropriate culture conditions in vitro. The pluripotency maintenance and proliferation of these cells are delicately governed by the concert effect of a complex transcriptional regulatory network. Herein, we discovered that p57Kip2 (p57), a cyclin-dependent kinase inhibitor canonically inhibiting cell proliferation, played a role in suppressing the pluripotency state of mouse ESCs (mESCs). p57 knockdown significantly stimulated the expressions of core pluripotency factors NANOG, OCT4, and SOX2, while p57 overexpression inhibited the expressions of these factors in mESCs. In addition, consistent with its function in somatic cells, p57 suppressed mESC proliferation. Further analysis showed that p57 could interact with and contribute to the activation of p53 in mESCs. In conclusion, the present study showed that p57 could antagonize the pluripotency state and the proliferation process of mESCs. This finding uncovers a novel function of p57 and provides new evidence for elucidating the complex regulatory of network of mESC fate.