Plasma metabolomics signatures of developmental dysplasia of the hip in Tibet plateau.

BACKGROUND: Developmental dysplasia of the hip (DDH) is a common childhood health complaint, whose etiology is multifactorial. The incidence of DDH is variable and higher in Tibet plateau. Here, we collected plasma samples and studied the metabolomics signatures of DDH. METHODS: Fifty babies were enrolled: 25 with DDH and 25 age-matched non-DDH healthy controls (HC group). We collected plasma samples, laboratory parameters and conducted untargeted metabolomics profiling. RESULTS: There are many differential metabolites among patients with DDH, including 4-ß-hydroxymethyl-4-α-methyl-5-α-cholest-7-en-3-beta-ol, ß-cryptoxanthin, α-tocopherol, taurocholic acid, glycocholic acid, 2-(3,4-dihydroxybenzoyloxy)-4,6-dihydroxybenzoate, arabinosylhypoxanthine, leucyl-hydroxyproline, hypoxanthine. The main differential metabolic pathways focused on primary bile acid biosynthesis, arginine and proline metabolism, phenylalanine metabolism, histidine metabolism, purine metabolism. CONCLUSIONS: To our knowledge, this is the first report of metabolomics profile in babies with DHH. By combining the α-tocopherol and taurocholic acid, we could achieve the differential diagnosis of DDH.

Effectiveness of data-augmentation on deep learning in evaluating rapid on-site cytopathology at endoscopic ultrasound-guided fine needle aspiration.

Rapid on-site cytopathology evaluation (ROSE) has been considered an effective method to increase the diagnostic ability of endoscopic ultrasound-guided fine needle aspiration (EUS-FNA); however, ROSE is unavailable in most institutes worldwide due to the shortage of cytopathologists. To overcome this situation, we created an artificial intelligence (AI)-based system (the ROSE-AI system), which was trained with the augmented data to evaluate the slide images acquired by EUS-FNA. This study aimed to clarify the effects of such data-augmentation on establishing an effective ROSE-AI system by comparing the efficacy of various data-augmentation techniques. The ROSE-AI system was trained with increased data obtained by the various data-augmentation techniques, including geometric transformation, color space transformation, and kernel filtering. By performing five-fold cross-validation, we compared the efficacy of each data-augmentation technique on the increasing diagnostic abilities of the ROSE-AI system. We collected 4059 divided EUS-FNA slide images from 36 patients with pancreatic cancer and nine patients with non-pancreatic cancer. The diagnostic ability of the ROSE-AI system without data augmentation had a sensitivity, specificity, and accuracy of 87.5%, 79.7%, and 83.7%, respectively. While, some data-augmentation techniques decreased diagnostic ability, the ROSE-AI system trained only with the augmented data using the geometric transformation technique had the highest diagnostic accuracy (88.2%). We successfully developed a prototype ROSE-AI system with high diagnostic ability. Each data-augmentation technique may have various compatibilities with AI-mediated diagnostics, and the geometric transformation was the most effective for the ROSE-AI system.

Nanoparticles of adaptive supramolecular networks self-assembled from nucleotides and lanthanide ions.

Amorphous nanoparticles of supramolecular coordination polymer networks are spontaneously self-assembled from nucleotides and lanthanide ions in water. They show intrinsic functions such as energy transfer from nucleobase to lanthanide ions and excellent performance as contrast enhancing agents for magnetic resonance imaging (MRI). Furthermore, adaptive inclusion properties are observed in the self-assembly process: functional materials such as fluorescent dyes, metal nanoparticles, and proteins are facilely encapsulated. Dyes in these nanoparticles fluoresce in high quantum yields with a single exponential decay, indicating that guest molecules are monomerically wrapped in the network. Gold nanoparticles and ferritin were also wrapped by the supramolecular shells. In addition, these nucleotide/lanthanide nanoparticles also serve as scaffolds for immobilizing enzymes. The adaptive nature of present supramolecular nanoparticles provides a versatile platform that can be utilized in a variety of applications ranging from material to biomedical sciences. As examples, biocompatibility and liver-directing characteristics in in vivo tissue localization experiments are demonstrated.