Search

Hepatocytes synthesize a vast number of glycoproteins found in their membranes and secretions, many of which contain O-glycans linked to Ser/Thr residues. As the functions and distribution of O-glycans on hepatocyte-derived membrane glycoproteins and blood glycoproteins are not well understood, we generated mice with a targeted deletion of Cosmc (C1Galt1c1) in hepatocytes. Liver glycoproteins in WT mice express typical sialylated core 1 O-glycans (T antigen/CD176) (Galβ1-3GalNAcα1-O-Ser/Thr), whereas the Cosmc knockout hepatocytes (HEP- Cosmc -KO) lack extended O-glycans and express the Tn antigen (CD175) (GalNAcα1-O-Ser/Thr). Tn-containing glycoproteins occur in the sera of HEP- Cosmc -KO mice but not in WT mice. The LDL-receptor (LDLR), a well-studied O-glycosylated glycoprotein in hepatocytes, behaves as a ∼145kD glycoprotein in WT liver lysates, whereas it is reduced to ∼120 kDa in lysates from HEP- Cosmc -KO mice. Interestingly, the expression of the LDLR, as well as HMG-CoA reductase, which is typically altered in response to dysregulated cholesterol metabolism, are similar between WT and HEP- Cosmc -KO mice, indicating no significant effect by Cosmc deletion on either LDLR stability or cholesterol metabolism. Consistent with this, we observed no detectable phenotype in the HEP- Cosmc -KO mice regarding development, appearance or aging compared to WT. These results provide surprising, novel information about the pathway of O-glycosylation in the liver. [ABSTRACT FROM AUTHOR]

This study examines the spatial spillover effects of transportation infrastructure on regional economic growth, utilizing panel data from 31 provincial-level administrative divisions in China from 2003 to 2022. Using the spatial Durbin model (SDM) and three distinct spatial weight matrices—0–1 adjacency, spatial economic–geographical nested, and GDP-based economic distance matrices—this study comprehensively analyzes the multifaceted impacts of transportation infrastructure. The results show that transportation infrastructure significantly promotes economic growth in both local and neighboring regions across all spatial weight matrices. The total effect is most pronounced in geographically proximate regions, with a coefficient of 7.845 (p < 0.01). Regions with similar economic development levels also show strong collaborative effects, with a coefficient of 2.074 (p < 0.01), although the marginal effect of transportation infrastructure diminishes. Furthermore, adjustments in industrial structure and innovation inputs demonstrate a short-term inhibitory effect on economic growth, highlighting the need for synchronized development of transportation infrastructure alongside industrial and innovation policies. This study incorporates multi-dimensional spatial weight matrices to systematically reveal the direct and indirect impacts of transportation infrastructure on regional economies, providing essential empirical support for regional coordination and infrastructure investment policies. The findings offer valuable insights for infrastructure planning in other regions, particularly in formulating policies that promote cross-regional economic cooperation and optimize resource allocation. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a common neurological degenerative disease. Collapsin response mediator protein2 ( CRMP2) plays an important role in the progression of AD. Hyperphosphorylation of CRMP2 results in decreased stability of axonal terminal microtubules and abnormal axoplasmic transport of neurons, which leads to abnormal mitochondrial dynamics of neurons, inhibits the ability of lysosomal autophagy, and leads to excessive activation of NMDA receptors. The phosphorylation of CRMP2 provides a new idea for AD drug development. In this review, the molecular mechanisms of CRMP2 involved in AD are reviewed, which can provide references for the development of targeted drugs. [ABSTRACT FROM AUTHOR]

Traffic jamming can easily lead to wasting time and fuel consumption and induce traffic accidents, thus seriously affecting daily life. In this study, an urban traffic flow cellular automaton (CA) model with random update rules is proposed to analyze the influence of network size and the probabilities of the change of the motion directions of cars, from up to right (p[sub.ur]) and from right to up (p[sub.ru]) on traffic flow. Simulation results show that, as the size of the system increases, the critical density tends to decrease causing larger phase transition, and for a larger size network system, the critical density is stable. The greater the p[sub.ur] and p[sub.ru], the greater the average velocity of vehicles, which means increase in the opportunity that vehicle change directions effectively avoids the formation of traffic jamming. By studying the operational status of urban traffic flow from the microlevel, it can provide some new ideas for alleviating urban traffic jamming., Author(s): Cheng Da [1]; Yongsheng Qian (corresponding author) [1]; Junwei Zeng [1]; Yongzhi Zhang [1]; Dejie Xu [1] 1. Introduction With the development of the economy and the increase of [...]