The reciprocal interaction between influenza virus and host microRNAs (miRNAs) has been implicated in the regulation of viral replication and host tropism. However, the global roles of the cellular miRNA repertoire and the mechanisms of miRNA-mediated antiviral defense await further elucidation. In this study, we systematically screened 297 cellular miRNAs from human and mouse epithelial cells and identified five inhibitory miRNAs that efficiently inhibited influenza virus replication in vitro and in vivo. Among these miRNAs, hsa-mir-127-3p, hsa-mir-486-5p, hsa-mir-593-5p, and mmu-mir-487b-5p were found to target at least one viral gene segment of both the human seasonal influenza H3N2 and the attenuated PR8 (H1N1) virus, whereas hsa-miR-1-3p inhibited viral replication by targeting the supportive host factor ATP6V1A. Moreover, the number of miRNA binding sites in viral RNA segments was positively associated with the activity of host miRNA-induced antiviral defense. Treatment with a combination of the five miRNAs through agomir delivery pronouncedly suppressed viral replication and effectively improved protection against lethal challenge with PR8 in mice. These data suggest that the highly expressed miRNAs in respiratory epithelial cells elicit effective antiviral defenses against influenza A viruses and will be useful for designing miRNA-based therapies against viral infection.
Significant inherent extra-articular varus angulation is associated with abnormal postoperative hip-knee-ankle (HKA) angle. At present, HKA is manually measured by orthopedic surgeons and it increases the doctors' workload. To automatically determine HKA, a deep learning-based automated method for measuring HKA on the unilateral lower limb X-rays was developed and validated. This study retrospectively selected 398 double lower limbs X-rays during 2018 and 2020 from Jilin University Second Hospital. The images (n = 398) were cropped into unilateral lower limb images (n = 796). The deep neural network was used to segment the head of hip, the knee, and the ankle in the same image, respectively. Then, the mean square error of distance between each internal point of each organ and the organ's boundary was calculated. The point with the minimum mean square error was set as the central point of the organ. HKA was determined using the coordinates of three organs' central points according to the law of cosines. In a quantitative analysis, HKA was measured manually by three orthopedic surgeons with a high consistency (176.90 ° ± 12.18°, 176.95 ° ± 12.23°, 176.87 ° ± 12.25°) as evidenced by the Kandall's W of 0.999 (p < 0.001). Of note, the average measured HKA by them (176.90 ° ± 12.22°) served as the ground truth. The automatically measured HKA by the proposed method (176.41 ° ± 12.08°) was close to the ground truth, showing no significant difference. In addition, intraclass correlation coefficient (ICC) between them is 0.999 (p < 0.001). The average of difference between prediction and ground truth is 0.49°. The proposed method indicates a high feasibility and reliability in clinical practice.
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