Automated Assessment of the Pulmonary Artery-to-Ascending Aorta Ratio in Fetal Cardiac Ultrasound Screening Using Artificial Intelligence.

The three-vessel view (3VV) is a standardized transverse scanning plane used in fetal cardiac ultrasound screening to measure the absolute and relative diameters of the pulmonary artery (PA), ascending aorta (Ao), and superior vena cava, as required. The PA/Ao ratio is used to support the diagnosis of congenital heart disease (CHD). However, vascular diameters are measured manually by examiners, which causes intra- and interobserver variability in clinical practice.

Local vaginal bioelectrical impedance can predict preterm delivery in mice.

Preterm birth is a serious pregnancy complication that affects neonatal mortality, morbidity, and long-term neurological prognosis. Predicting spontaneous preterm delivery (PTD) is important for its management. While excluding the risk of PTD is important, identifying women at high risk of PTD is imperative for medical intervention.

Severe hemolysis, elevated liver enzymes, and low platelet syndrome requiring differentiation of thrombotic microangiopathy: Four cases from a nationwide survey in Japan.

Severe cases of hemolysis, elevated liver enzymes, and low platelet (HELLP) syndrome requiring plasma exchange or dialysis should be differentiated from other thrombotic microangiopathy (TMA) and treated appropriately. To evaluate the prevalence and clinical characteristics of such cases in Japan, a questionnaire-based survey was conducted among obstetricians who are members of the Perinatal Research Network Group in Japan. There were a total of 335 cases of HELLP syndrome over a 3-year period in the 48 facilities that responded to the survey.

Medical Professional Enhancement Using Explainable Artificial Intelligence in Fetal Cardiac Ultrasound Screening.

Diagnostic support tools based on artificial intelligence (AI) have exhibited high performance in various medical fields. However, their clinical application remains challenging because of the lack of explanatory power in AI decisions (black box problem), making it difficult to build trust with medical professionals. Nevertheless, visualizing the internal representation of deep neural networks will increase explanatory power and improve the confidence of medical professionals in AI decisions.

Model-Agnostic Method for Thoracic Wall Segmentation in Fetal Ultrasound Videos.

The application of segmentation methods to medical imaging has the potential to create novel diagnostic support models. With respect to fetal ultrasound, the thoracic wall is a key structure on the assessment of the chest region for examiners to recognize the relative orientation and size of structures inside the thorax, which are critical components in neonatal prognosis. In this study, to improve the segmentation performance of the thoracic wall in fetal ultrasound videos, we proposed a novel model-agnostic method using deep learning techniques: the Multi-Frame + Cylinder method (MFCY).

Image Segmentation of the Ventricular Septum in Fetal Cardiac Ultrasound Videos Based on Deep Learning Using Time-Series Information.

Image segmentation is the pixel-by-pixel detection of objects, which is the most challenging but informative in the fundamental tasks of machine learning including image classification and object detection. Pixel-by-pixel segmentation is required to apply machine learning to support fetal cardiac ultrasound screening; we have to detect cardiac substructures precisely which are small and change shapes dynamically with fetal heartbeats, such as the ventricular septum. This task is difficult for general segmentation methods such as DeepLab v3+, and U-net.

Proline might have been the first amino acid in the primitive genetic code.

Stereochemical assignment of amino acids and corresponding codons or anticodons has not been successful so far. Here, we focused on proline and GGG (anticodon of tRNA(Pro)) and investigated their mutual interaction. Circular dichroism spectroscopy revealed that guanosine nucleotides (GG, GGG) formed G-quartet structures.