Van Lang University

Tumor stemness is increasingly recognized as a key contributor to tumor heterogeneity, immune regulation, and therapeutic resistance in colorectal cancer (CRC). In this study, we developed a stemness-based risk model using bulk transcriptomic data from The Cancer Genome Atlas and evaluated its prognostic and therapeutic relevance through integrative analyses. The proposed risk score robustly stratified patients into distinct prognostic groups and remained an independent predictor of overall survival after adjustment for clinicopathological variables. Stemness-high tumors exhibited altered immune infiltration patterns and coordinated upregulation of immune checkpoint-related genes. Although the association between stemness score and immune evasion potential was modest, its clinical relevance was supported by validation in independent immunotherapy-treated cohorts, where low-risk patients demonstrated improved survival and higher response rates. Single-cell RNA sequencing (scRNA-seq) analysis further revealed that enhanced stemness and dedifferentiation were predominantly localized within malignant epithelial cells. Together, these findings establish tumor stemness as a central determinant of prognosis, immune regulation, and therapeutic vulnerability in CRC.

Urban expansion in subtropical metropolitan regions intensifies land use/land cover (LULC) transformations and alters land surface temperature (LST) dynamics, directly affecting urban climate resilience and environmental sustainability. This study evaluates historical LULC and LST changes (1995–2017) and predicts future scenarios (2028–2039) in Porto Alegre, southern Brazil, using Landsat imagery integrated with a Cellular Automata–Artificial Neural Network (CA-ANN) model implemented in the MOLUSCE platform. LULC maps were generated using supervised Maximum Likelihood Classification. Model validation achieved an overall accuracy of 77.6

This study investigates the radioprotective efficacy of a combinatorial liposomal formulation encapsulating silibinin (Lip-SIL) and α-tocopherol (Lip-TOC) on human fibroblasts (HF cells) against X-ray induced damage. Lip-SIL and Lip-TOC were synthesized via thin-film hydration and sonication. Radioprotective effects on HF cells exposed to 2 Gy X-rays were evaluated using Annexin V-FITC/PI (apoptosis), CM-H2DCFDA (intracellular ROS), Trypan blue (viability), and γH2AX (DNA double-strand breaks) assays. The combined treatment of Lip-SIL (10 µg/mL) and Lip-TOC (10 µg/mL) demonstrated enhanced protective efficacy compared to individual treatments. Specifically, the combination reduced the cell death rate to 6.50 ± 0.70

Purpose: This study examines the impact of digital transformation on the competitive advantage of logistics enterprises, with a focus on the mediating roles of customer participation and innovation. Customer participation is highlighted as a key mechanism enabling enterprises to co-create service value, enhance customer experience, and foster innovation. Research design, data, and methodology: A quantitative approach was adopted using survey data from 380 managers in logistics enterprises in Ho Chi Minh City, Vietnam. Structural equation modeling (SEM) was employed to test the proposed relationships among digital transformation, customer participation, innovation, and competitive advantage. Results: The findings demonstrate that digital transformation has both direct and indirect effects on competitive advantage through customer participation and innovation. Additionally, IT infrastructure, digital leadership capability, organizational agility, competitive pressure, and government support positively influence digital transformation. Conclusions: The study underscores the central role of digital transformation in enhancing competitive advantage. It further emphasizes customer participation as a catalyst for innovation and value co-creation. These findings contribute empirical evidence to the literature and provide practical implications for logistics enterprises seeking to implement digital transformation effectively and sustain competitiveness in a dynamic market environment.

This paper explores the energy efficiency (EE) of integrated sensing and communication (ISAC) systems employing massive multiple-input multiple-output (mMIMO) techniques to leverage spatial beamforming gains for both communication and sensing. We focus on an mMIMO-ISAC system operating in an orthogonal frequency-division multiplexing setting with a uniform planar array, zero-forcing downlink transmission, and mono-static radar sensing to exploit multi-carrier channel diversity. By deriving closed-form expressions for the achievable communication rate and Cram & eacute;r-Rao bounds (CRBs), we are able to determine the overall EE in closed-form. A power allocation problem is then formulated to maximize the system's EE by balancing communication and sensing efficiency while satisfying communication rate requirements and CRB constraints. Through a detailed analysis of CRB properties, we reformulate the problem into a more manageable form and leverage Dinkelbach's and successive convex approximation (SCA) techniques to develop an efficient iterative algorithm. A novel initialization strategy is also proposed to ensure high-quality feasible starting points for the iterative optimization process. Extensive simulations demonstrate the significant performance improvement of the proposed approach over baseline approaches. Results further reveal that as communication spectral efficiency rises, the influence of sensing EE on the overall system EE becomes more pronounced, even in sensing-dominated scenarios. Specifically, in the high omega regime of 2 & times;10(-3) , we observe a 16.7% reduction in overall EE when spectral efficiency increases from 4 to 8 bps/Hz, despite the system being sensing-dominated.