Slow flow HD and traditional CDFI technologies in identifying pulmonary veins in the first trimester.

OBJECTIVE: This study aims to assess the feasibility and effectiveness of color doppler flow imaging (CDFI) technology and the Slow Flow HD imaging technique in identifying fetal pulmonary veins (PVs) in the first trimester (11-13 + 6 weeks), and further explore the factors affecting fetal pulmonary vein identification in early pregnancy. METHODS: Echocardiography and scanning of PVs were performed in 240 normal singleton fetuses in early pregnancy by using CDFI and slow flow HD techniques, to compare the ability of two methods to identify the PVs. Slow Flow HD technology was used to further investigate the difference of PVs identification at different gestational ages [group I (11-11 + 6 weeks), group II (12-12 + 6 weeks), group III (13-13 + 6 weeks)] and with different maternal body mass indices (BMI) (≥ 25 and < 25). In 31 cases of 240 fetuses, transvaginal ultrasonography was added due to maternal habitus or significant retroversion of the uterus, and the difference in PVs identification between transabdominal and transvaginal examination was analyzed. RESULTS: Successful PVs identification rates via CDFI and Slow Flow HD were 32.0% and 88.3%, respectively (p < 0.05). The identification rate of at least one and two pulmonary veins in Slow Flow HD was 88.3% and 76.2%, and all four pulmonary veins in 11.6% (p < 0.05). The identification rate of group I, II and III were 76.4%, 88.9% and 96.0%, respectively. The identification rate was 45.1% in the transabdominal ultrasound group and 83.8% in the transvaginal ultrasound group. The identification rate was 62.5% in the BMI ≥ 25 group and 94.7% in the BMI < 25 group (p < 0.05). CONCLUSIONS: Slow Flow HD can detect PVs in early pregnancy more often than using CDFI. Slow Flow HD is a feasible and effective imaging technique for evaluating PVs in early pregnancy.

Chromosome Three-Dimensional Structure Reconstruction: An Iterative ShRec3D Algorithm.

The three-dimensional (3D) structure of chromosomes is of great significance to ensure that the genome performs various functions (e.g., gene expression) correctly and replicates and separates correctly in mitosis. Since the emergence of Hi-C in 2009, a new experimental technique in molecular biology, researchers have been paying more and more attention to the reconstruction of chromosome 3D structure. To reconstruct the 3D structure of chromosomes based on Hi-C experimental data, many algorithms have been proposed, among which ShRec3D is one of the most outstanding. In this article, an iterative ShRec3D algorithm is presented to greatly improve the native ShRec3D algorithm. Experimental results show that our algorithm can significantly promote the performance of ShRec3D, and this improvement is applicable to almost all data noise range and signal coverage range, so it is universal.