In vivo ultrasound localization microscopy for high-density microbubbles.

Ultrasound Localization Microscopy (ULM) surpasses the constraints imposed by acoustic diffraction, achieving sub-wavelength resolution visualization of microvasculature through the precise localization of minute microbubbles (MBs). Nonetheless, the analysis of densely populated regions with overlapping MB point spread responses introduces significant localization errors, limiting the use of technique to low-concentration conditions. This raises a trade-off issue between localization efficiency and MB density. In this work, we present a new deep learning framework that combines Transformer and U-Net architectures, termed ULM-TransUNet. As a non-linear model, it is able to learn the complex data patterns of overlapping MBs in dense conditions for accurate localization. To evaluate the performance of ULM-TransUNet, a series of numerical simulations and in vivo experiments are carried out. Numerical simulation results indicate that ULM-TransUNet achieves high-quality ULM imaging, with improvements of 21.93 % in detection rate, 17.36 % in detection precision, and 20.53 % in detection sensitivity, compared to previous state-of-the-art deep learning (DL) method (e.g., ULM-UNet). For the in vivo experiments, ULM-TransUNet achieves the highest spatial resolution (9.4 µm) and rapid inference speed (26.04 ms/frame). Furthermore, it consistently detects more small vessels and resolves closely spaced vessels more effectively. The outcomes of this work imply that ULM-TransUNet can potentially enhance the microvascular imaging performance on high-density MB conditions.

Sulfated Polysaccharides from Sea Cucumber Cooking Liquid Prevents Obesity by Modulating Gut Microbiome, Transcriptome, and Metabolite Profiles in Mice Fed a High-Fat Diet.

We aimed to explore the anti-obesity mechanism from the microbiome, metabolome, and transcriptome viewpoints, focusing on the sulfated polysaccharides found in the cooking liquid of Apostichopus japonicus (CLSPAJ) to explore the potential mediators of the anti-obesity effects in mice fed a high-fat diet (HFD). The mice treated with CLSPAJ showed a decrease in obesity and blood lipid levels. Gut microbiome dysbiosis caused by the HFD was reversed after CLSPAJ supplementation, along with increased levels of indole-3-ethanol, N-2-succinyl-L-glutamic acid 5-semialdehyde, and urocanic acid. These increases were positively related to the increased Akkermansia, Lactobacillus, Roseburia, and Phascolarctobacterium. Transcriptome analysis showed that B cell receptor signaling and cytochrome P450 xenobiotic metabolism were the main contributors to the improvement in obesity. Metabolome-transcriptome analysis revealed that CLSPAJ reversal of obesity was mainly due to amino acid metabolism. These findings suggest that CLSPAJ could be a valuable prebiotic preparation for preventing obesity-related diseases.

Virtual Screening of FDA-Approved Drugs for Enhanced Binding with Mitochondrial Aldehyde Dehydrogenase.

Mitochondrial aldehyde dehydrogenase (ALDH2) is a potential target for the treatment of substance use disorders such as alcohol addiction. Here, we adopted computational methods of molecular dynamics (MD) simulation, docking, and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analysis to perform a virtual screening of FDA-approved drugs, hitting potent inhibitors against ALDH2. Using MD-derived conformations as receptors, butenafine (net charge q = +1 e) and olaparib (q = 0) were selected as promising compounds with a low toxicity and a binding strength equal to or stronger than previously reported potent inhibitors of daidzin and CVT-10216. A few negatively charged compounds were also hit from the docking with the Autodock Vina software, while the MM-PBSA analysis yielded positive binding energies (unfavorable binding) for these compounds, mainly owing to electrostatic repulsion in association with a negatively charged receptor (q = -6 e for ALDH2 plus the cofactor NAD+). This revealed a deficiency of the Vina scoring in dealing with strong charge-charge interactions between binding partners, due to its built-in protocol of not using atomic charges for electrostatic interactions. These observations indicated a requirement of further verification using MD and/or MM-PBSA after docking prediction. The identification of key residues for the binding implied that the receptor residues at the bottom and entrance of the substrate-binding hydrophobic tunnel were able to offer additional interactions with different inhibitors such as π-π, π-alkyl, van der Waals contacts, and polar interactions, and that the rational use of these interactions is beneficial to the design of potent inhibitors against ALDH2.