Incorporation of 5-fluorouracil into U2 snRNA blocks pseudouridylation and pre-mRNA splicing in vivo

5-fluorouracil (5FU) is an effective anti-cancer drug, yet its mechanism of action remains unclear. Here, we examine the effect of 5FU on pre-mRNA splicing in vivo. Using RT–PCR, we show that the splicing of a number of pre-mRNAs is inhibited in HeLa cells that have been exposed to a low dose of 5FU. It appears that this inhibitory effect is not due to its incorporation into pre-mRNA, because partially or fully 5FU-substituted pre-mRNA, when injected into Xenopus oocytes, is spliced just as well as is the unsubstituted pre-mRNA. Detailed analyses of 5FU-treated cells indicate that 5FU is incorporated into U2 snRNA at important naturally occurring pseudouridylation sites. Remarkably, 5FU incorporation effectively blocks the formation of important pseudouridines in U2 snRNA, as only a trace of pseudouridine is detected when cells are exposed to a low dose of 5FU for 5 days. Injection of the hypopseudouridylated HeLa U2 snRNA into U2-depleted Xenopus oocytes fails to reconstitute pre-mRNA splicing, whereas control U2 isolated from untreated or uracil-treated HeLa cells completely reconstitutes the splicing. Our results demonstrate for the first time that 5FU incorporates into a spliceosomal snRNA at natural pseudouridylation sites in vivo, thereby inhibiting snRNA pseudouridylation and splicing. This mechanism may contribute substantially to 5FU-mediated cell death

Poly[bis­[μ-1,4-bis­(imidazol-1-ylmeth­yl)benzene]dichloridocadmium(II)]

The title compound, [CdCl2(C14H14N4)2]n, has a slightly distorted octa­hedral coordination geometry, formed by four N atoms from 1,4-bis­(imidazol-1-ylmeth­yl)benzene ligands and two Cl atoms, giving a two-dimensional network. The Cd atom lies on a centre of inversion

ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase Transition

Neural message passing is a basic feature extraction unit for graph-structured data considering neighboring node features in network propagation from one layer to the next. We model such process by an interacting particle system with attractive and repulsive forces and the Allen-Cahn force arising in the modeling of phase transition. The dynamics of the system is a reaction-diffusion process which can separate particles without blowing up. This induces an Allen-Cahn message passing (ACMP) for graph neural networks where the numerical iteration for the particle system solution constitutes the message passing propagation. ACMP which has a simple implementation with a neural ODE solver can propel the network depth up to one hundred of layers with theoretically proven strictly positive lower bound of the Dirichlet energy. It thus provides a deep model of GNNs circumventing the common GNN problem of oversmoothing. GNNs with ACMP achieve state of the art performance for real-world node classification tasks on both homophilic and heterophilic datasets.Comment: 26 pages, 5 figures. NeurIPS 2022 Workshop on GLFrontiers (Oral). ICLR 2023 (Spotlight

Effect of Metformin on Lactate Metabolism in Normal Hepatocytes under High Glucose Stress in Vitro

Objective To study the effect of metformin on lactate metabolism in hepatocytes in vitro under high glucose stress. In vitro LO2 cells, liver cells were randomly divided into blank control group, 25 tendency/L glucose solution, 27 tendency/L glucose solution,29 tendency/L glucose solution, 31 tendency/L glucose solution, 33 tendency/L glucose solution,35 tendency/L glucose solution treatment group, the optimal concentration of 31 tendency after L, use 30 tendency for L metformin solution, and then divided into blank control group, the optimal concentration of glucose solution, normal liver cells + metformin solution normal liver cells. The optimal concentration of glucose solution normal liver cells + metformin solution respectively in the 12 h, 24 h,48 h on cell count plate to calculate the number of liver cells, and using lactic acid determination kit the optimal concentration of glucose solution + normal liver cells and normal liver cells + the optimal concentration of glucose solution + metformin solution respectively in the 12 h, 24 h, 48 h of cell cultures of lactic acid value. There was no significant change in the lactic acid concentration but significant increase in the number of surviving hepatocytes in the highglycemic control group compared with that in the high-glycemic control group without metformin. Metformin has no significant effect on lactic acid metabolism of hepatocytes under high glucose stress in vitro, and has a protective effect on hepatocytes under high glucose stress. Based on this,it is preliminarily believed that metformin is not the direct factor leading to diabetic lactic acidosis

A self-induced mechanism of large-scale helical structures in compressible turbulent flows

A novel self-sustaining mechanism is proposed for large-scale helical structures in compressible turbulent flows. The existence of two channels of subgrid-scale and viscosity terms for large-scale helicity evolution is confirmed for the first time, through selecting a physical definition of the large-scale helicity in compressible turbulence. Under the influence of the fluid element expansion, it is found that the helicity is generated at small scales via the second-channel viscosity, and the inverse cross-scale helicity transfers at inertial scales through the second-channel helicity flux. Together, they form a self-induced mechanism, which provides a physical insight into the long-period characteristic of large-scale helical structures in the evolution of compressible flow systems