Zongmeng Zhang^1,2,#, Cai Chen^3,#, Shaorui Rui³, Conghan Li³, Jiong Gu^3,*, Liang He^3,*

BIOCELL, DOI:10.32604/biocell.2025.073085

Abstract Objective: Hepatocellular carcinoma (HCC) ranks among the most prevalent malignant tumors globally. Metabolically associated fatty liver disease is a significant risk factor for HCC. Adiponectin, a key regulatory protein in glucolipid metabolism, presents potential as an anti-tumor target in HCC cells. The study focused on evaluating the anti-HCC properties of AdipoRon, an agonist of the adiponectin receptor. Method: Cell viability and proliferation were assessed using the cell counting kit-8 and colony formation assays, respectively. AdipoRon’s effect on HCC cell damage was evaluated via flow cytometry, apoptosis, and (lactate dehydrogenase) LDH assays. Mitochondrial function was evaluated… More >

Keiko Yanagihara^1,*, Masato Yoshida², Kensaku Awaji², Tamami Yamakawa¹, Sena Kato¹, Miki Tamura¹, Koji Nagata³

Oncology Research, DOI:10.32604/or.2025.073891

Abstract Background: Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors have transformed the management of hormone receptor–positive/HER2–negative (HR+/HER2–) advanced breast cancer, yet evidence for elderly or poor-performance patients remains limited. This study examined real-world outcomes of palbociclib plus endocrine therapy in Asian patients, with additional subgroup analyses by age and performance status. Methods: We retrospectively analyzed 46 consecutive Asian patients with recurrent or de novo HR+/HER2− breast cancer treated with first-line palbociclib plus ET between April 2021 and March 2025. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall response rate (ORR), disease control rate (DCR), and safety.… More >

Jianfa Wu^1,2,3, Huang Chen³, Sihong Wang^1,2, Lei Peng^1,2, Xiaoying Hu^1,2, Zhou Liu^1,2,*

Oncology Research, DOI:10.32604/or.2025.070542

Abstract Objectives: Ribosomal protein S6 kinase A2 (RPS6KA2) has been identified as a potential prognostic biomarker in several cancers, including breast cancer, glioblastoma, and prostate cancer. However, its functional significance in ovarian cancer is not well characterized. This study was designed to explore the therapeutic relevance of modulating RPS6KA2 in the context of ovarian cancer, particularly in relation to cisplatin resistance. Methods: The expression levels of RPS6KA2 and key regulators involved in autophagy and ferroptosis were assessed using quantitative reverse transcription-PCR, immunofluorescence staining, immunohistochemistry, and western blotting. Prognostic associations were conducted using the Kaplan-Meier Plotter database.… More >

Yongle Qiu^1,#, Kunshan Li^1,#, Wenjing Wang¹, Wenjuan Zhang², Jilun Liu², Yang Bai³, Fei Xu³, Jie Guo^1,*

Oncology Research, DOI:10.32604/or.2025.069612

Abstract Background: The regulatory mechanisms governing vasculogenic mimicry (VM) in oral squamous cell carcinoma (OSCC) remain largely undefined. This study aimed to identify critical factors and elucidate the epigenetic mechanisms underlying VM in OSCC. Methods: Bioinformatics analysis was performed utilizing single-cell RNA-seq, bulk RNA-seq, and histone H3 lysine 27 acetylation (H3K27ac) Chromatin Immunoprecipitation (ChIP)-seq data obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. ChIP-qPCR was used to validate the binding of ETS transcription factor ELK4 (ELK4) to the dihydrofolate reductase (DHFR) enhancer. In vitro VM formation and invasion of OSCC cells were… More > Graphic Abstract

Jiling Song¹, Hua Wang^2,*, Jianbing Guo¹, Minghua Lin², Bin Zheng^2,*, Jiqiang Wu^3,*

Journal of Polymer Materials, DOI:10.32604/jpm.2025.073414

Abstract The pursuit of safer energy storage systems is driving the development of advanced electrolytes for lithium-ion batteries. Traditional liquid electrolytes pose flammability risks, while solid-state alternatives often suffer from low ionic conductivity. Gel polymer electrolytes (GPEs) emerge as a promising compromise, combining the safety of solids with the ionic conductivity of liquids. Cellulose, an abundant and eco-friendly polymer, presents an ideal base material for sustainable GPEs due to its biocompatibility and mechanical strength. This study systematically investigates how drying methods affect cellulose-based GPEs. Cellulose hydrogels were synthesized through dissolution-crosslinking and processed using vacuum drying (VD),… More >

Jinyou Qiu^1,2, Jiale Liu^1,2, Yubing Li^1,2,*, Shaogeng Zhong³, Guilong Dai^1,2, Wenhua Liu⁴

Frontiers in Heat and Mass Transfer, DOI:10.32604/fhmt.2025.072260

Abstract The growing demand for energy-saving and renewable heating solutions has made photovoltaic/thermal (PV/T) heat pump systems a promising technology. However, their thermal and electrical performance, as well as the overall utilization of solar energy, strongly depend on capacity configuration and operating parameters. To address this issue, this study proposes a PV/T heat pump system featuring a novel rhombic flow channel structure that functions as the collector-evaporator. An experimental test bench was established to evaluate system performance, and a one-dimensional numerical model was developed to investigate the effects of environmental and operating parameters. The simulation results… More >

Wenfei Yi¹, Mingzhong Zheng¹, Jiayi Wang², Hao Yang^2,*, Zhenglong Sun²

Energy Engineering, DOI:10.32604/ee.2025.072770

Abstract With the growing integration of renewable energy sources (RESs) and smart interconnected devices, conventional distribution networks have turned to active distribution networks (ADNs) with complex system model and power flow dynamics. The rapid fluctuation of RES power may easily result in frequent voltage violation issues. Taking the flexible RES reactive power as control variables, this paper proposes a two-layer control scheme with Koopman wide neural network (WNN) based model predictive control (MPC) method for optimal voltage regulation and network loss reduction. Based on Koopman operator theory, a data-driven WNN method is presented to fit a… More >

Damodharan Palaniappan¹, Tan Kuan Tak², K. Vijayan³, Balajee Maram⁴, Pravin R Kshirsagar⁵, Naim Ahmad^6,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.073387

Abstract A phase-aware cross-modal framework is presented that synthesizes UWF_FA from non-invasive UWF_RI for diabetic retinopathy (DR) stratification. A curated cohort of 1198 patients (2915 UWF_RI and 17,854 UWF_FA images) with strict registration quality supports training across three angiographic phases (initial, mid, final). The generator is based on a modified pix2pixHD with an added Gradient Variance Loss to better preserve microvasculature, and is evaluated using MAE, PSNR, SSIM, and MS-SSIM on held-out pairs. Quantitatively, the mid phase achieves the lowest MAE (98.76 ± 42.67), while SSIM remains high across phases. Expert review shows substantial agreement (Cohen’s More >

Mubashir Ali^1,2, Jingzhen Li¹, Zedong Nie^1,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.073048

Abstract Diabetes imposes a substantial burden on global healthcare systems. Worldwide, nearly half of individuals with diabetes remain undiagnosed, while conventional diagnostic techniques are often invasive, painful, and expensive. In this study, we propose a noninvasive approach for diabetes detection using photoplethysmography (PPG), which is widely integrated into modern wearable devices. First, we derived velocity plethysmography (VPG) and acceleration plethysmography (APG) signals from PPG to construct multi-channel waveform representations. Second, we introduced a novel multiset spatiotemporal feature fusion framework that integrates hand-crafted temporal, statistical, and nonlinear features with recursive feature elimination and deep feature extraction using… More >

Changyu Jeon, Younghoon Kim^*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.073030

Abstract Accurate State-of-Health (SOH) prediction is critical for the safe and efficient operation of lithium-ion batteries (LiBs). However, conventional methods struggle with the highly nonlinear electrochemical dynamics and declining accuracy over long-horizon forecasting. To address these limitations, this study proposes CIPF-Informer, a novel digital twin framework that integrates the Informer architecture with Channel Independence (CI) and a Particle Filter (PF). The CI mechanism enhances robustness by decoupling multivariate state dependencies, while the PF captures the complex stochastic variations missed by purely deterministic models. The proposed framework was evaluated using the Massachusetts Institute of Technology (MIT) battery More >