Subjects conceived through assisted reproductive technologies (ART) potentially suffer from impaired left ventricular (LV) function due to premature vascular aging. This study aimed to evaluate whether subtle differences in LV diastolic function can be observed echocardiographically between young ART subjects and their spontaneously conceived peers. The echocardiographic assessment included the measurement of LV dimensions, mitral inflow velocities, and myocardial velocity at early diastole (E', cm/s) at the LV wall and the interventricular septum (IVS). An average from E/E'LV and E/E'IVS (E/E'AVG) was derived. In total, 66 ART subjects and 83 controls (12.85 ± 5.80 years vs. 13.25 ± 5.89 years, = 0.677) were included. The ART subjects demonstrated a significantly lower E'LV (19.29 ± 3.29 cm/s vs. 20.67 ± 3.78 cm/s, = 0.020) compared to their spontaneously conceived peers. Study participants of ≥ 10 years of age displayed a significantly higher E/E'AVG (6.50 ± 0.97 vs. 6.05 ± 0.99, = 0.035) within the ART cohort. The results of this study demonstrate a significantly lower LV diastolic function in the ART subjects. However, no significant changes in LV diastolic function were observed between the two groups when the results were adjusted for age, birth weight percentile, and gestational age. Those ART subjects born preterm might have an elevated risk of developing LV diastolic alterations and could therefore profit from close echocardiographic monitoring.
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http://dx.doi.org/10.3390/jcm11237128 | DOI Listing |
Rev Sci Instrum
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Shenyang Bluewisdom Technology Co., Ltd., Shenyang, Liaoning Province 110623, China.
Existing lower limb exoskeletons (LLEs) have demonstrated a lack of sufficient patient involvement during rehabilitation training. To address this issue and better incorporate the patient's motion intentions, this paper proposes an online brain-computer interface (BCI) system for LLE based motor imagery and stacked ensemble. The establishment of this online BCI system enables a comprehensive closed-loop control process, which includes the collection and decoding of brain signals, robotic control, and real-time feedback mechanisms.
View Article and Find Full Text PDFCureus
December 2024
Department of Obstetrics and Gynecology, Shiga University of Medical Science, Ostu, JPN.
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View Article and Find Full Text PDFZhongguo Xue Xi Chong Bing Fang Zhi Za Zhi
December 2024
School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 210000, China.
Objective: To investigate the incidence of anemia and evaluate the immune status among newly reported HIV/AIDS patients in Jiangsu Province in 2021, and to identify the risk factors of anemia among patients living with HIV infections.
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Methods
January 2025
School of Computer Science, Qufu Normal University, Rizhao 276826, China.
Brain imaging genetics aims to explore the association between genetic factors such as single nucleotide polymorphisms (SNPs) and brain imaging quantitative traits (QTs). However, most existing methods do not consider the nonlinear correlations between genotypic and phenotypic data, as well as potential higher-order relationships among subjects when identifying bi-multivariate associations. In this paper, a novel method called deep hyper-Laplacian regularized self-representation learning based structured association analysis (DHRSAA) is proposed which can learn genotype-phenotype associations and obtain relevant biomarkers.
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
School of Software, Jiangxi Normal University, Nanchang, 330022, China.
Source-free domain adaptation (SFDA) has become crucial in medical image analysis, enabling the adaptation of source models across diverse datasets without labeled target domain images. Self-training, a popular SFDA approach, iteratively refines self-generated pseudo-labels using unlabeled target domain data to adapt a pre-trained model from the source domain. However, it often faces model instability due to incorrect pseudo-label accumulation and foreground-background class imbalance.
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