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Introduction: Glioblastoma (GBM) is a highly aggressive brain tumor characterized by pronounced invasiveness, rapid progression, frequent recurrence, and poor clinical prognosis. Current treatment strategies remain inadequate due to the lack of effective molecular targets, underscoring the urgent need to identify novel therapeutic avenues.
Methods: In this study, we employed weighted gene co-expression network analysis and meta-analysis, incorporating clinical immunotherapy datasets, to identify ten candidate genes associated with GBM initiation, progression, prognosis, and response to immunotherapy. Multi-omics analyses across glioma and pan-cancer datasets revealed that these genes play pivotal roles in cancer biology.
Results: Phospholipase Cb4 (PLCB4) showed a negative correlation with tumor grade in clinical samples, suggesting its potential role as a tumor suppressor. Evidence indicated that PLCB4 expression is modulated by Wnt signaling, and its overexpression may activate the calcium ion signaling pathway. Notably, is strongly associated with aberrant tumor proliferation, making it a compelling therapeutic target. Through structure-based virtual screening, five small molecules with high predicted affinity for were identified as potential drug candidates.
Discussion: This study's integrative approach-combining target identification, pathway inference, and in silico drug screening-offers a promising framework for rational drug development in GBM. The findings may reduce unnecessary experimental screening and medical costs, and represent a significant step toward improving therapeutic outcomes and prognosis for GBM patients.
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http://dx.doi.org/10.3389/fimmu.2025.1610683 | DOI Listing |
Clin J Am Soc Nephrol
September 2025
The George Institute for Global Health, University of New South Wales, Sydney, Australia.
Background: Substantial advances have been made in therapeutics for IgA nephropathy. We conducted a systematic review and meta-analysis to evaluate the comparative efficacy and safety of existing and novel IgA nephropathy therapies.
Methods: We searched MEDLINE and Embase databases from inception to May 21, 2025 for Phase 2b and 3 multi-center, randomized, placebo-controlled trials enrolling patients with IgA nephropathy that reported treatment effects on proteinuria and/or estimated glomerular filtration rate (eGFR) slope.
Acad Radiol
September 2025
Department of Urology, the Second Affiliated Hospital of Kunming Medical University, Kunming, China (H.S., Q.W., S.F., H.W.). Electronic address:
Rationale And Objectives: This study systematically evaluates the diagnostic performance of artificial intelligence (AI)-driven and conventional radiomics models in detecting muscle-invasive bladder cancer (MIBC) through meta-analytical approaches. Furthermore, it investigates their potential synergistic value with the Vesical Imaging-Reporting and Data System (VI-RADS) and assesses clinical translation prospects.
Methods: This study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
Front Oncol
August 2025
Department of Hepatobiliary Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Background: Early diagnosis can significantly improve survival rate of Pancreatic ductal adenocarcinoma (PDAC), but due to the insidious and non-specific early symptoms, most patients are not suitable for surgery when diagnosed. Traditional imaging techniques and an increasing number of non-imaging diagnostic methods have been used for the early diagnosis of pancreatic cancer (PC) through deep learning (DL).
Objective: This review summarizes diagnosis methods for pancreatic cancer with the technique of deep learning and looks forward to the future development directions of deep learning for early diagnosis of pancreatic cancer.
medRxiv
August 2025
The Windreich Department of Artificial Intelligence and Human Health, Mount Sinai Medical Center, NY, USA.
Background: AI agents built on large language models (LLMs) can plan tasks, use external tools, and coordinate with other agents. Unlike standard LLMs, agents can execute multi-step processes, access real-time clinical information, and integrate multiple data sources. There has been interest in using such agents for clinical and administrative tasks, however, there is limited knowledge on their performance and whether multi-agent systems function better than a single agent for healthcare tasks.
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September 2025
Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 201204, China.
Background: Recurrent spontaneous abortion (RSA) poses a significant clinical challenge for childbearing women. Cyclosporine A (CsA), first introduced by our group for RSA treatment, has gained wide clinical application in China, yet remains underutilized internationally. With this systematic review, we aimed to systematically evaluate the efficacy and safety of CsA based therapy in the management of RSA.
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