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Shen, Hong

Publications and source records attributed to Shen, Hong.

Identification and Clinical Evaluation of Potential Biomarkers for Breast Cancer Resistance Protein ( BCRP / ABCG2 )

Clinical inhibition and genetic variation of the Breast Cancer Resistance Protein (BCRP/ABCG2) efflux transporter can significantly influence drug exposure, highlighting the need for reliable BCRP functional biomarkers. This study aimed to identify and evaluate biomarkers predictive of BCRP function in humans. A comprehensive analysis of metabolomic genome‐wide association studies (mGWAS) was conducted to discover potential BCRP biomarkers, followed by evaluation inin vitrotransporter assays and a clinical drug–drug interaction (DDI) study. Across multiple mGWAS datasets, plasma concentrations of three herbicide derivatives—4‐hydroxychlorothalonil (4HC), 3‐bromo‐5‐chloro‐2,6‐dihydroxybenzoic acid (BCDBA), and 3,5‐dichloro‐2,6‐dihydroxybenzoic acid (DCDBA)—were significantly elevated (P < 5E‐8) in individuals carrying reduced functionABCG2polymorphisms. These compounds were confirmed as novel BCRP substrates via transporter uptake assays and selected for clinical evaluation alongside riboflavin, a known BCRP substrate and potential BCRP biomarker. In a DDI study with 11 healthy subjects, eltrombopag, a BCRP inhibitor, increased rosuvastatin concentrations by approximately twofold (P = 0.002). No significant changes in the plasma concentrations of organic anion transporting polypeptide 1B (OATP1B) biomarkers (CP‐I and CP‐III) or potential BCRP biomarkers (4HC, BCDBA, DCDBA, or riboflavin) were observed. Notably, two subjects were heterozygous carriers for theABCG2p.Q141K variant and exhibited significantly higher baseline concentrations of 4HC (P = 0.004) and BCDBA (P = 0.0003), consistent with reduced BCRP function. These findings suggest that 4HC and BCDBA are promising biomarkers for baseline BCRP function in specific populations, such as those harboring reduced function genetic polymorphisms, but do not appear suitable for detecting acute BCRP inhibition.

Pharmacology & Pharmacy↗

Traditional Chinese Medicine Alleviates Ulcerative Colitis via Modulating Gut Microbiota

Ulcerative colitis (UC) is a chronic inflammatory bowel disorder characterized by relapsing and remitting inflammation of the bowel. In recent decades, traditional Chinese medicine (TCM) has been widely used in the therapy of UC. However, its underlying mechanisms have not been sufficiently elucidated. Accumulating studies indicate that the gut microbial dysbiosis is closely related to UC. It has been demonstrated that TCM could alter the composition of intestinal microbiota by enriching beneficial and SCFA-producing bacteria and reducing pathogenic bacteria. In this review, we discussed recent evidence regarding the TCM and its role in modulating gut microbiota for the treatment of UC.

Feng, Wan↗

Neural network potential for Zr–Rh system by machine learning

Zr–Rh metallic glass has enabled its many applications in vehicle parts, sports equipment and so on due to its outstanding performance in mechanical property, but the knowledge of the microstructure determining the superb mechanical property remains yet insufficient. Here, we develop a deep neural network potential of Zr–Rh system by using machine learning, which breaks the dilemma between the accuracy and efficiency in molecular dynamics simulations, and greatly improves the simulation scale in both space and time. Here, the results show that the structural features obtained from the neural network method are in good agreement with the cases in ab initio molecular dynamics simulations. Furthermore, we build a large model of 5400 atoms to explore the influences of simulated size and cooling rate on the melt-quenching process of Zr 77 Rh 23 . Our study lays a foundation for exploring the complex structures in amorphous Zr 77 Rh 23 , which is of great significance for the design and practical application.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A deep learning interatomic potential developed for atomistic simulation of carbon materials

Interatomic potentials based on neural-network machine learning method have attracted considerable attention in recent years owing to their outstanding ability to balance the accuracy and efficiency in atomistic simulations. In this work, a neural-network potential (NNP) for carbon is generated to simulate the structural properties of various carbon structures. The potential is trained using a database consisting of crystalline and liquid structures obtained by the first-principles density functional theory (DFT) calculations. The developed potential accurately predicts the energies and forces in crystalline and liquid carbon structures, the energetic stability of defected graphene, and the structures of amorphous carbon as the function of density. As a result, the excellent accuracy and transferability of the NNP provide a promising tool for accurate atomistic simulations of various carbon materials with faster speed and much lower cost.

36 MATERIALS SCIENCE↗

Selective inhibition of cullin 3 neddylation through covalent targeting DCN1 protects mice from acetaminophen-induced liver toxicity

Cullin-RING E3 ligases (CRLs) regulate the turnover of approximately 20% of mammalian cellular proteins. Neddylation of individual cullin proteins is essential for the activation of each CRL. We report herein the discovery of DI-1548 and DI-1859 as two potent, selective and covalent DCN1 inhibitors. These inhibitors selectively inhibit neddylation of cullin 3 in cells at low nanomolar concentrations and are 2–3 orders of magnitude more potent than our previously reported reversible DCN1 inhibitor. Mass spectrometric analysis and co-crystal structures reveal that these compounds employ a unique mechanism of covalent bond formation with DCN1. DI-1859 induces a robust increase of NRF2 protein, a CRL3 substrate, in mouse liver and effectively protects mice from acetaminophen-induced liver damage. Taken together, this study demonstrates the therapeutic potential of selective inhibition of cullin neddylation.

59 BASIC BIOLOGICAL SCIENCES↗

Luminescence mechanism in hydrogenated silicon quantum dots with a single oxygen ligand

Though photoluminescence (PL) of Si quantum dots (QDs) has been known for decades and both theoretical and experimental studies have been extensive, their luminescence mechanism has not been elaborated. Several models have been proposed to explain the mechanism. A deep insight into the origin of light emissions in Si QDs is necessary. This work calculated the ground- and excited state properties of hydrogenated Si QDs with various diameters, including full hydrogen passivation, single Si=O ligands, single epoxide and coexisting Si=O and epoxide structures in order to investigate the dominant contribution states for luminescence. The results revealed that even a single oxygen atom in hydrogenated Si QDs can dramatically change their electronic and optical properties. Intriguingly, we found that a size-independent emission, the strongest among all possible emissions, was induced by the single Si=O passivated Si-QDs. In non-oxidized Si-QDs exhibiting a core-related size-tunable emission, the luminescence properties can be modulated by the ligands of Si QDs, and a very small number of oxygen ligands can strongly influence the luminescence of nanocrystalline silicon. Our findings deepen the understanding of the PL mechanism of Si QDs and can further promote the development of silicon-based optoelectronic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗