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Differentiated thyroid cancer is the most frequently diagnosed endocrine tumor. While differentiated thyroid cancers often respond to initial treatment, little is known about the differences in circulating immune cells amongst patients who respond differently. A prospective study of 39 patients with differentiated thyroid cancer was conducted. Serum thyroglobulin levels and thyroid and immunological functions were tested before and after radioactive iodine treatment (RAIT). Efficacy assessments were performed 6 to 12 months after radioactive iodine treatment. Most patients showed an excellent response to radioactive iodine treatment. Before radioactive iodine treatment, the excellent response group had considerably fewer circulating CD4 + T cell subsets than the non-excellent response group. Both the excellent response and non-excellent response groups had considerably lower circulating CD4 + T lymphocyte subsets 30 days after radioactive iodine treatment, but those of the excellent response group were still lower than those of the non-excellent response group. All circulating CD4 + T cell subsets in the excellent response group rose by varying degrees by the 90th day, but only Treg cell amounts increased in the non-excellent response group. Interestingly, in the non-excellent response group, we noticed a steady drop in Th1 cells. However, the bulk of circulating CD4 + T cell subsets between the two groups did not differ appreciably by the 90th day. Finally, we discovered that CD4 + T cell subsets had strong predictive potential, and we thus developed high-predictive-performance models that deliver more dependable prognostic information. In conclusion, in individuals with differentiated thyroid cancer, there is great variation in circulating immune cells, resulting in distinct treatment outcomes. Low absolute CD4 + T cell counts is linked to improved clinical outcomes as well as stronger adaptive and resilience capacities., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflict of interest., (Copyright © 2022 Shi, Zhang, Li, Fan, Xue, Cheng, Wu, Lu, Wu, Li, Liu and Li.)

The spatial interaction of chromosomes is regarded as an important issue affecting the regulation of gene expression, and the high-throughput chromosome conformation capture (Hi-C) technology has become the primary tool to explore the temporal and spatial interactions of chromosomes in three-dimensional genomics. With the continuous accumulation of Hi-C samples and the increasing complexity of pipelines, the bioinformatic analysis of Hi-C data has been considered an opportunity and a challenge for understanding the spatial regulation mechanism of gene expression. In this paper, the current status and development outline of bioinformatic methods for Hi-C data are introduced, including data normalization, multi-level structure analysis, data visualization and 3D modeling, especially of multi-level structure at A/B compartments, topological associated domains (TADs) and chromain looping levels. Based on this, we provide the outlook of future hotspots and trends in this area. Hopefully our insight will be beneficial for the exploration of gene expression regulation from the traditional linear model to the 3D mode.