Endothelial Cell-Specific Molecule 2 (Ecsm2) Localizes To Cell-Cell Junctions And Modulates Bfgf-Directed Cell Migration Via The Erk-Fak Pathway

Background: Despite its first discovery by in silico cloning of novel endothelial cell-specific genes a decade ago, the biological functions of endothelial cell-specific molecule 2 (ECSM2) have only recently begun to be understood. Limited data suggest its involvement in cell migration and apoptosis. However, the underlying signaling mechanisms and novel functions of ECSM2 remain to be explored. Methodology/Principal Findings: A rabbit anti-ECSM2 monoclonal antibody (RabMAb) was generated and used to characterize the endogenous ECSM2 protein. Immunoblotting, immunoprecipitation, deglycosylation, immunostaining and confocal microscopy validated that endogenous ECSM2 is a plasma membrane glycoprotein preferentially expressed in vascular endothelial cells (ECs). Expression patterns of heterologously expressed and endogenous ECSM2 identified that ECSM2 was particularly concentrated at cell-cell contacts. Cell aggregation and transwell assays showed that ECSM2 promoted cell-cell adhesion and attenuated basic fibroblast growth factor (bFGF)-driven EC migration. Gain or loss of function assays by overexpression or knockdown of ECSM2 in ECs demonstrated that ECSM2 modulated bFGF-directed EC motility via the FGF receptor (FGFR)-extracellular regulated kinase (ERK)-focal adhesion kinase (FAK) pathway. The counterbalance between FAK tyrosine phosphorylation (activation) and ERK-dependent serine phosphorylation of FAK was critically involved. A model of how ECSM2 signals to impact bFGF/FGFR-driven EC migration was proposed. Conclusions/Significance: ECSM2 is likely a novel EC junctional protein. It can promote cell-cell adhesion and inhibit bFGF-mediated cell migration. Mechanistically, ECSM2 attenuates EC motility through the FGFR-ERK-FAK pathway. The findings suggest that ECSM2 could be a key player in coordinating receptor tyrosine kinase (RTK)-, integrin-, and EC junctional component-mediated signaling and may have important implications in disorders related to endothelial dysfunction and impaired EC junction signaling. © 2011 Shi et al

Spatial and temporal evolution characteristics and influencing factors of carbon footprint pressure in China's equipment manufacturing industry

IntroductionThe equipment manufacturing industry is a key source of industrial carbon emissions in China. To assess its environmental impact comprehensively, this study introduces the concept of carbon footprint pressure (ECFP) integrating both carbon sources and vegetation carbon sinks.MethodsBased on provincial panel data from 2003 to 2020, the study combines LMDI decomposition, Tapio decoupling, and extended STIRPAT spatial econometric models to analyze temporal and spatial evolution patterns and influencing factors.ResultsThe ECFP in China's equipment manufacturing industry shows an overall upward trend, spreading from coastal to inland provinces. Employment, economic expansion, and technological effects are key drivers. Some eastern regions achieve weak decoupling between economic growth and ECFP, while central and western regions show unstable coupling.DiscussionGreen technology innovation and industrial upgrading can mitigate ECFP both locally and across neighboring regions. The results provide a theoretical basis for regional emission reduction and coordinated low-carbon development

Immunogenicity and Protective Efficacy against Murine Tuberculosis of a Prime-Boost Regimen with BCG and a DNA Vaccine Expressing ESAT-6 and Ag85A Fusion Protein

Heterologous prime-boost regimens utilizing BCG as a prime vaccine probably represent the best hope for the development of novel tuberculosis (TB) vaccines. In this study, we examined the immunogenicity and protective efficacy of DNA vaccine (pcD685A) expressing the fusion protein of Ag85A and ESAT-6 (r685A) and its booster effects in BCG-immunized mice. The recombinant r685A fusion protein stimulated higher level of antigen-specific IFN-γ release in tuberculin skin test- (TST-) positive healthy household contacts of active pulmonary TB patients than that in TST-negative population. Vaccination of C57BL/6 mice with pcD685A resulted in significant protection against challenge with virulent Mycobacterium tuberculosis H37Rv when compared with the control group. Most importantly, pcD685A could act as a BCG booster and amplify Th1-type cell-mediated immunity in the lung of BCG-vaccinated mice as shown the increased expression of IFN-γ. The most significant reduction in bacterial load of both spleen and lung was obtained in mice vaccinated with BCG prime and pcD685A DNA booster when compared with BCG or pcD685A alone. Thus, our study indicates that pcD685A may be an efficient booster vaccine against TB with a strong ability to enhance prior BCG immunity

UNIT: Unifying Image and Text Recognition in One Vision Encoder

Currently, vision encoder models like Vision Transformers (ViTs) typically excel at image recognition tasks but cannot simultaneously support text recognition like human visual recognition. To address this limitation, we propose UNIT, a novel training framework aimed at UNifying Image and Text recognition within a single model. Starting with a vision encoder pre-trained with image recognition tasks, UNIT introduces a lightweight language decoder for predicting text outputs and a lightweight vision decoder to prevent catastrophic forgetting of the original image encoding capabilities. The training process comprises two stages: intra-scale pretraining and inter-scale finetuning. During intra-scale pretraining, UNIT learns unified representations from multi-scale inputs, where images and documents are at their commonly used resolution, to enable fundamental recognition capability. In the inter-scale finetuning stage, the model introduces scale-exchanged data, featuring images and documents at resolutions different from the most commonly used ones, to enhance its scale robustness. Notably, UNIT retains the original vision encoder architecture, making it cost-free in terms of inference and deployment. Experiments across multiple benchmarks confirm that our method significantly outperforms existing methods on document-related tasks (e.g., OCR and DocQA) while maintaining the performances on natural images, demonstrating its ability to substantially enhance text recognition without compromising its core image recognition capabilities

Protective Role of Nuclear Factor E2-Related Factor 2 against Acute Oxidative Stress-Induced Pancreatic β

Oxidative stress is implicated in the pathogenesis of pancreatic β-cell dysfunction that occurs in both type 1 and type 2 diabetes. Nuclear factor E2-related factor 2 (NRF2) is a master regulator in the cellular adaptive response to oxidative stress. The present study found that MIN6 β-cells with stable knockdown of Nrf2 (Nrf2-KD) and islets isolated from Nrf2-knockout mice expressed substantially reduced levels of antioxidant enzymes in response to a variety of stressors. In scramble MIN6 cells or wild-type islets, acute exposure to oxidative stressors, including hydrogen peroxide (H2O2) and S-nitroso-N-acetylpenicillamine, resulted in cell damage as determined by decrease in cell viability, reduced ATP content, morphology changes of islets, and/or alterations of apoptotic biomarkers in a concentration- and/or time-dependent manner. In contrast, silencing of Nrf2 sensitized MIN6 cells or islets to the damage. In addition, pretreatment of MIN6 β-cells with NRF2 activators, including CDDO-Im, dimethyl fumarate (DMF), and tert-butylhydroquinone (tBHQ), protected the cells from high levels of H2O2-induced cell damage. Given that reactive oxygen species (ROS) are involved in regulating glucose-stimulated insulin secretion (GSIS) and persistent activation of NRF2 blunts glucose-triggered ROS signaling and GSIS, the present study highlights the distinct roles that NRF2 may play in pancreatic β-cell dysfunction that occurs in different stages of diabetes

A prognostic 15-gene model based on differentially expressed genes among metabolic subtypes in diffuse large B-cell lymphoma

The outcomes of patients with diffuse large B-cell lymphoma (DLBCL) vary widely, and about 40% of them could not be cured by the standard first-line treatment, R-CHOP, which could be due to the high heterogeneity of DLBCL. Here, we aim to construct a prognostic model based on the genetic signature of metabolic heterogeneity of DLBCL to explore therapeutic strategies for DLBCL patients. Clinical and transcriptomic data of one training and four validation cohorts of DLBCL were obtained from the GEO database. Metabolic subtypes were identified by PAM clustering of 1,916 metabolic genes in the 7 major metabolic pathways in the training cohort. DEGs among the metabolic clusters were then analyzed. In total, 108 prognosis-related DEGs were identified. Through univariable Cox and LASSO regression analyses, 15 DEGs were used to construct a risk score model. The overall survival (OS) and progression-free survival (PFS) of patients with high risk were significantly worse than those with low risk (OS: HR 2.86, 95%CI 2.04–4.01, p < 0.001; PFS: HR 2.42, 95% CI 1.77–3.31, p < 0.001). This model was also associated with OS in the four independent validation datasets (GSE10846: HR 1.65, p = 0.002; GSE53786: HR 2.05, p = 0.02; GSE87371: HR 1.85, p = 0.027; GSE23051: HR 6.16, p = 0.007) and PFS in the two validation datasets (GSE87371: HR 1.67, p = 0.033; GSE23051: HR 2.74, p = 0.049). Multivariable Cox analysis showed that in all datasets, the risk model could predict OS independent of clinical prognosis factors (p < 0.05). Compared with the high-risk group, patients in the low-risk group predictively respond to R-CHOP (p = 0.0042), PI3K inhibitor (p < 0.05), and proteasome inhibitor (p < 0.05). Therefore, in this study, we developed a signature model of 15 DEGs among 3 metabolic subtypes, which could predict survival and drug sensitivity in DLBCL patients