Clustering single-cell RNA sequencing data via iterative smoothing and self-supervised discriminative embedding.

Single-cell transcriptome sequencing (scRNA-seq) is a high-throughput technique used to study gene expression at the single-cell level. Clustering analysis is a commonly used method in scRNA-seq data analysis, helping researchers identify cell types and uncover interactions between cells. However, the choice of a robust similarity metric in the clustering procedure is still an open challenge due to the complex underlying structures of the data and the inherent noise in data acquisition. Here, we propose a deep clustering method for scRNA-seq data called scRISE (scRNA-seq Iterative Smoothing and self-supervised discriminative Embedding model) to resolve this challenge. The model consists of two main modules: an iterative smoothing module based on graph autoencoders designed to denoise the data and refine the pairwise similarity in turn to gradually incorporate cell structural features and enrich the data information; and a self-supervised discriminative embedding module with adaptive similarity threshold for partitioning samples into correct clusters. Our approach has shown improved quality of data representation and clustering on seventeen scRNA-seq datasets against a number of state-of-the-art deep learning clustering methods. Furthermore, utilizing the scRISE method in biological analysis against the HNSCC dataset has unveiled 62 informative genes, highlighting their potential roles as therapeutic targets and biomarkers.

Discovery of a novel SHP2 allosteric inhibitor using virtual screening, FMO calculation, and molecular dynamic simulation.

CONTEXT: SHP2 is a non-receptor protein tyrosine phosphatase to remove tyrosine phosphorylation. Functionally, SHP2 is an essential bridge to connect numerous oncogenic cell-signaling cascades including RAS-ERK, PI3K-AKT, JAK-STAT, and PD-1/PD-L1 pathways. This study aims to discover novel and potent SHP2 inhibitors using a hierarchical structure-based virtual screening strategy that combines molecular docking and the fragment molecular orbital method (FMO) for calculating binding affinity (referred to as the Dock-FMO protocol). For the SHP2 target, the FMO method prediction has a high correlation between the binding affinity of the protein-ligand interaction and experimental values (R2 = 0.55), demonstrating a significant advantage over the MM/PBSA (R2 = 0.02) and MM/GBSA (R2 = 0.15) methods. Therefore, we employed Dock-FMO virtual screening of ChemDiv database of ∼2,990,000 compounds to identify a novel SHP2 allosteric inhibitor bearing hydroxyimino acetamide scaffold. Experimental validation demonstrated that the new compound (E)-2-(hydroxyimino)-2-phenyl-N-(piperidin-4-ylmethyl)acetamide (7188-0011) effectively inhibited SHP2 in a dose-dependent manner. Molecular dynamics (MD) simulation analysis revealed the binding stability of compound 7188-0011 and the SHP2 protein, along with the key interacting residues in the allosteric binding site. Overall, our work has identified a novel and promising allosteric inhibitor that targets SHP2, providing a new starting point for further optimization to develop more potent inhibitors. METHODS: All the molecular docking studies were employed to identify potential leads with Maestro v10.1. The protein-ligand binding affinities of potential leads were further predicted by FMO calculations at MP2/6-31G* level using GAMESS v2020 system. MD simulations were carried out with AmberTools18 by applying the FF14SB force field. MD trajectories were analyzed using VMD v1.9.3. MM/GB(PB)SA binding free energy analysis was carried out with the mmpbsa.py tool of AmberTools18. The docking and MD simulation results were visualized through PyMOL v2.5.0.

A theoretical study on the effect of C60 particles on the growth of coronene radical based on HACA pathway.

Soot is a pollutant caused by combustion and is harmful to the environment and human health. Polycyclic aromatic hydrocarbons (PAHs) are considered the precursors of soot, thus exploring the growth mechanism of PAHs is conducive to reducing soot release. The mechanism by which a pentagonal carbon ring triggers the formation of curved PAHs has been demonstrated but studies on subsequent growth of soot are rare due to the lack of a suitable model. Buckminsterfullerene (C60), as one of the products from incomplete combustion under specific conditions, is similar in structure to soot particles with a surface that can be treated as curved PAH. Coronene (C24H12) is a typical seven-membered fused-ring PAH. In this study, C60 was employed as a substitute for soot particles to investigate its effect on coronene growth reaction based on the hydrogen-abstraction/acetylene-addition (HACA) mechanism. Density functional theory (DFT) at the M062X/6-31G(d,p) level was adopted to investigate the potential energy surfaces (PESs) for these reactions. The high-pressure limiting rate constants for the relevant reactions were obtained based on transition state theory. The calculated results indicate that C60 is easily hydrogenated, providing new pathways for coronene growth. Soot particles have a certain effect on the growth of PAHs. This study provides favorable support for further understanding the effect of soot on the growth pathway of PAHs.

Directional Manipulation of Electron Transfer by Energy Level Engineering for Efficient Cathodic Oxygen Reduction.

Electron transfer plays an important role in determining the energy conversion efficiency of energy devices. Nitrogen-coordinated single metal sites (M-N4) materials as electrocatalysts have exhibited great potential in devices. However, there are still great difficulties in how to directionally manipulate electron transfer in M-N4 catalysts for higher efficiency. Herein, we demonstrated the mechanism of electron transfer being affected by energy level structure based on classical iron phthalocyanine (FePc) molecule/carbon models and proposed an energy level engineering strategy to manipulate electron transfer, preparing high-performance ORR catalysts. Engineering molecular energy level via modulating FePc molecular structure with nitro induces a strong interfacial electronic coupling and efficient charge transfer from carbon to FePc-ß-NO2 molecule. Consequently, the assembled zinc-air battery exhibits ultrahigh performance which is superior to most of M-N4 catalysts. Energy level engineering provides a universal approach for directionally manipulating electron transfer, bringing a new concept to design efficient and stable M-N4 electrocatalyst.

The associations between ethnicity and outcomes of infants in neonatal intensive care units.

OBJECTIVE: To determine the associations between maternal ethnicity and outcomes of infants born between 22 and 31 weeks' gestation and admitted to neonatal intensive care units in New South Wales and the Australian Capital Territory, Australia, between 1995 and 2006. DESIGN AND PATIENTS: De-identified perinatal and neonatal outcome data for 10 267 infants were examined. There were 8629 (84.0%) Caucasian, 922 (9.0%) Asian, 439 (4.3%) indigenous, 127 (1.2%) Polynesian and Maori (PAM) and 150 (1.5%) infants of other maternal ethnicities (excluded from study). Caucasians were the referent for all comparisons. RESULTS: Infants of indigenous mothers were less likely to receive antenatal steroids and three times as likely to be born in non-tertiary hospitals (OR 3.28, 95% CI 2.59 to 4.16, p<0.001). PAM infants were more likely to have Apgar scores <7 at 5 min of age (1.76, 95% CI 1.16 to 2.67, p<0.01). Asian infants had lower birth weight (mean±SD 44.7±27.9, p<0.001) and head circumference percentiles (47.8±29.0, p<0.001), were more likely to be small for gestational age (1.53, 95% CI 1.25 to 1.88, p<0.001), less likely to have hyaline membrane disease (0.78, 95% CI 0.68 to 0.90, p<0.001) but had a higher risk of severe retinopathy of prematurity (1.52, 95% CI 1.11 to 2.07, p<0.01). Ethnicity did not influence infant mortality. CONCLUSIONS: Neonatal growth characteristics and morbidity but not mortality are influenced by maternal ethnicity. Of concern is the risk of low Apgar scores in PAM infants and non-tertiary births of indigenous infants. Review of perinatal care for certain vulnerable ethnic populations is recommended due to the rapidly changing ethnic compositions of many countries around the world.