Insight into the interaction between amino acids and SO2: Detailed bonding modes.

CONTEXT: Amino acids are a highly effective and environmentally friendly adsorbent for SO2. However, there has been no comprehensive study of the binding modes between amino acids and SO2 at the molecular level. In this paper, the binding modes of three amino acids (Asp, Lys, and Val) with SO2 are studied comprehensively and in detail using quantum chemical calculations. The results indicate that each amino acid has multiple binding modes: 22 for Asp, 49 for Lys, and 10 for Val. Both the amino and carboxyl groups in amino acids, as well as those in side chains, can serve as binding sites for chalcogen bonds. The binding energies range from - 6.42 to - 1.06 kcal/mol for Asp, - 12.43 to - 1.63 kcal/mol for Lys, and - 7.42 to - 0.60 kcal/mol for Val. Chalcogen and hydrogen bonds play a crucial role in the stronger binding modes. The chalcogen bond is the strongest when interacting with an amino group, with an adiabatic force constant of 0.475 mDyn/Å. Energy decomposition analysis indicates that the interaction is primarily electrostatic attraction, with the orbital and dispersive interactions dependent on the binding mode. METHODS: Amino acids and complexes of amino acids with SO2 were used to do semi-empirical MD using Molclus combined with xtb at the GFN2 level. Optimization and frequency calculations of the structures were conducted using density-functional theory (DFT) B3LYP/6-311G* (with DFT-D3 correction). Single-point energy calculations were performed for all structures using DLPNO-CCSD(T)/aug-cc-pVTZ with tightPNO. Further analysis of the structures was conducted using ESP, AIM, IGMH, and sob-EDA to gain a deeper understanding of the interactions between amino acids and SO2.

Behind the Non-Uniform Breakup of Bubble Slug in Y-Shaped Microchannel: Dynamics and Mechanisms.

Bubble flow in confined geometries is a problem of fundamental and technological significance. Among all the forms, bubble breakup in bifurcated microchannels is one of the most commonly encountered scenarios, where an in-depth understanding is necessary for better leveraging the process. This study numerically investigates the non-uniform breakup of a bubble slug in Y-shaped microchannels under different flow ratios, Reynolds numbers, and initial bubble volumes. Overall, the bubble can either breakup or non-breakup when passing through the bifurcation and shows different forms depending on flow regimes. The flow ratio-Reynolds number phase diagrams indicate a power-law transition line of breakup and non-breakup. The bubble takes longer to break up with rising flow ratios yet breaks earlier with higher Reynolds numbers and volumes. Non-breakup takes less time than the breakup patterns. Flow ratio is the origin of non-uniform breakup. Both the Reynolds number and initial volume influence the bubble states when reaching the bifurcation and thus affect subsequent processes. Bubble neck dynamics are analyzed to describe the breakup further. The volume distribution after breaking up is found to have a quadratic relation with the flow ratio. Our study is hoped to provide insights for practical applications related to non-uniform bubble breakups.

An efficient molecular genetic testing strategy for incontinentia pigmenti based on single-tube long fragment read sequencing.

Incontinentia pigmenti (IP) is a rare X-linked dominant neuroectodermal dysplasia that primarily affects females. The only known causative gene is IKBKG, and the most common genetic cause is the recurrent IKBKG△4-10 deletion resulting from recombination between two MER67B repeats. Detection of variants in IKBKG is challenging due to the presence of a highly homologous non-pathogenic pseudogene IKBKGP1. In this study, we successfully identified four pathogenic variants in four IP patients using a strategy based on single-tube long fragment read (stLFR) sequencing with a specialized analysis pipeline. Three frameshift variants (c.519-3_519dupCAGG, c.1167dupC, and c.700dupT) were identified and subsequently validated by Sanger sequencing. Notably, c.519-3_519dupCAGG was found in both IKBKG and IKBKGP1, whereas the other two variants were only detected in the functional gene. The IKBKG△4-10 deletion was identified and confirmed in one patient. These results demonstrate that the proposed strategy can identify potential pathogenic variants and distinguish whether they are derived from IKBKG or its pseudogene. Thus, this strategy can be an efficient genetic testing method for IKBKG. By providing a comprehensive understanding of the whole genome, it may also enable the exploration of other genes potentially associated with IP. Furthermore, the strategy may also provide insights into other diseases with detection challenges due to pseudogenes.

WSA-MP-Net: Weak-signal-attention and multi-scale perception network for microvascular extraction in optical-resolution photoacoustic microcopy.

The unique advantage of optical-resolution photoacoustic microscopy (OR-PAM) is its ability to achieve high-resolution microvascular imaging without exogenous agents. This ability has excellent potential in the study of tissue microcirculation. However, tracing and monitoring microvascular morphology and hemodynamics in tissues is challenging because the segmentation of microvascular in OR-PAM images is complex due to the high density, structure complexity, and low contrast of vascular structures. Various microvasculature extraction techniques have been developed over the years but have many limitations: they cannot consider both thick and thin blood vessel segmentation simultaneously, they cannot address incompleteness and discontinuity in microvasculature, there is a lack of open-access datasets for DL-based algorithms. We have developed a novel segmentation approach to extract vascularity in OR-PAM images using a deep learning network incorporating a weak signal attention mechanism and multi-scale perception (WSA-MP-Net) model. The proposed WSA network focuses on weak and tiny vessels, while the MP module extracts features from different vessel sizes. In addition, Hessian-matrix enhancement is incorporated into the pre-and post-processing of the input and output data of the network to enhance vessel continuity. We constructed normal vessel (NV-ORPAM, 660 data pairs) and tumor vessel (TV-ORPAM, 1168 data pairs) datasets to verify the performance of the proposed method. We developed a semi-automatic annotation algorithm to obtain the ground truth for our network optimization. We applied our optimized model successfully to monitor glioma angiogenesis in mouse brains, thus demonstrating the feasibility and excellent generalization ability of our model. Compared to previous works, our proposed WSA-MP-Net extracts a significant number of microvascular while maintaining vessel continuity and signal fidelity. In quantitative analysis, the indicator values of our method improved by about 1.3% to 25.9%. We believe our proposed approach provides a promising way to extract a complete and continuous microvascular network of OR-PAM and enables its use in many microvascular-related biological studies and medical diagnoses.