Background and purpose: To investigate the feasibility of synthesizing computed tomography (CT) images from magnetic resonance (MR) images using generative adversarial networks (GANs) for nasopharyngeal carcinoma (NPC) intensity-modulated radiotherapy (IMRT) planning. Materials and methods: Conventional T1-weighted MR images and CT images were acquired from 173 NPC patients. The MR and CT images of 28 patients were randomly chosen as the independent tested set. The remaining images were used to build a conditional GAN (cGAN) and a cycle-consistency GAN (cycleGAN). A U-net was used as the generator in cGAN, whereas a residual-Unet was used as the generator in cycleGAN. The cGAN was trained using the deformable registered MR-CT image pairs, whereas the cycleGAN was trained using the unregistered MR and CT images. The generated synthetic CT (SCT) images from cGAN and cycleGAN were compared with the true CT images with respect to their Hounsfield Unit (HU) discrepancy and dosimetric accuracy for NPC IMRT plans. Results: The mean absolute errors within the body were 69.67 ± 9.27 HU and 100.62 ± 7.39 HU for the cGAN and cycleGAN, respectively. The 2%/2-mm c passing rates were (98.68 ± 0.94)% and (98.52 ± 1.13)% for the cGAN and cycleGAN, respectively. Meanwhile, the absolute dose discrepancies within the regions of interest were (0.49 ± 0.24)% and (0.62 ± 0.36)%, respectively. Conclusion: Both cGAN and cycleGAN could swiftly generate accurate SCT volume images from MR images, with high dosimetric accuracy for NPC IMRT planning. cGAN was preferable if high-quality MR-CT image pairs were available.

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The maturation of human stem cell-derived cardiomyocytes (hSC-CMs) has been a major challenge to further expand the scope of their application. Over the past years, several strategies have been proven to facilitate the structural and functional maturation of hSC-CMs, which include but are not limited to engineering the geometry or stiffness of substrates, providing favorable extracellular matrices, applying mechanical stretch, fluidic or electrical stimulation, co-culturing with niche cells, regulating biochemical cues such as hormones and transcription factors, engineering and redirecting metabolic patterns, developing 3D cardiac constructs such as cardiac organoid or engineered heart tissue, or culturing under in vivo implantation. In this review, we summarize these maturation strategies, especially the recent advancements, and discussed their advantages as well as the pressing problems that need to be addressed in future studies.

Purpose: To aid in the selection of a suitable combination of irradiation mode and jaw width in helical tomotherapy (HT) for the treatment of nasopharyngeal carcinoma (NPC). Materials and Methods:Twenty patients with NPC who underwent radiotherapy were retrospectively selected. Four plans using a jaw width of 2.5 or 5-cm in dynamic jaw (DJ) or fix jaw (FJ) modes for irradiation were designed (2.5DJ, 2.5FJ, 5.0DJ, and 5.0FJ). The dose parameters of planning target volume (PTV) and organs at risk (OARs) of the plans were compared and analyzed, as well as the beam on time (BOT) and monitor unit (MU). The plans in each group were ranked by scoring the doses received by the OARs and the superity was assessed in combination with the planned BOT and MU. Results:The prescribed dose coverage of PTV met the clinical requirements for all plans in the four groups. The groups using a 2.5-cm jaw width or a DJ mode provided better protection to most OARs, particularly for those at the longitudinal edges of the PTV (P < 0.05). The 2.5DJ group had the best ranking for OAR-dose, followed by the 2.5FJ and 5.0DJ groups with a same score. The BOT and MU of the groups using a 5.0-cm jaw width reduced nearly 45% comparing to those of the 2.5-cm jaw groups.Conclusion: 2.5DJ has the best dose distribution, while 5.0DJ has satisfactory dose distribution and less BOT and MU that related to the leakage dose. Both 2.5DJ or 5DJ were recommended for HT treatment plan for NPC based on the center workload.

With the arrival of the Internet + era and the need for development and personnel training, the traditional teaching model of TCM (Traditional Chinese Medicine) needs to be transformed into a mixed teaching mode. In addition, the TCM English teaching resources from which learners can pick are restricted, and certain critical revised TCM material is not delivered on time. For high-quality delivery of service to TCM English learners, a system with materials and communication is considered extremely important. In this connection, “Internet +” provides both possibilities and problems for the advancement of TCM English instruction, which has considered a key to advanced TCM. Therefore, motivated by the development of “Internet +,” we try to establish a relevant analysis of the mixed teaching model and propose the implementation path and method of the mixed teaching model of traditional Chinese medicine: changing ideas and guiding students to enter into deep learning to build a teaching community; integration and reform of online teaching and classroom teaching of traditional Chinese medicine; emphasis on developmental evaluation. The evaluation is based on whether it provides students with meaningful Chinese medicine learning experience and deep learning status as the evaluation criteria.