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Background: The standard of care for glioblastoma multiforme (GBM) is maximal surgical resection followed by conventional fractionated concurrent chemoradiotherapy (CCRT) with a total dose of 60 Gy. However, there is currently no consensus on the optimal boost technique for CCRT in GBM.
Methods: We conducted a retrospective review of 398 patients treated with CCRT between 2016 and 2021, using data from two institutional databases. Patients were divided into two groups: those receiving sequential boost (SEB, N = 119) and those receiving simultaneous integrated boost (SIB, N = 279). The primary endpoint was overall survival (OS). To minimize differences between the SIB and SEB groups, we conducted propensity score matching (PSM) analysis.
Results: The median follow-up period was 18.6 months. Before PSM, SEB showed better OS compared to SIB (2-year, 55.6% vs. 44.5%, p = 0.014). However, after PSM, there was no significant difference between two groups (2-year, 55.6% vs. 51.5%, p = 0.300). The boost sequence was not associated with inferior OS before and after PSM (all p-values > 0.05). Additionally, the rates of symptomatic pseudo-progression were similar between the two groups (odds ratio: 1.75, p = 0.055).
Conclusions: This study found no significant difference in OS between SEB and SIB for GBM patients treated with CCRT. Further research is needed to validate these findings and to determine the optimal boost techniques for this patient population.
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http://dx.doi.org/10.1007/s11060-023-04465-6 | DOI Listing |
PLoS One
September 2025
Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
View Article and Find Full Text PDFBrain Behav
September 2025
Department of Neurosurgery, First Medical Center of the Chinese PLA General Hospital, Beijing, People's Republic of China.
Background: The gut microbiota plays a crucial role in the development of glioma. With the evolution of artificial intelligence technology, applying AI to analyze the vast amount of data from the gut microbiome indicates the potential that artificial intelligence and computational biology hold in transforming medical diagnostics and personalized medicine.
Methods: We conducted metagenomic sequencing on stool samples from 42 patients diagnosed with glioma after operation and 30 non-intracranial tumor patients and developed a Gradient Boosting Machine (GBM) machine learning model to predict the glioma patients based on the gut microbiome data.
J Hazard Mater
September 2025
School of Environment and Geography, Qingdao University, Qingdao 266071, China; Carbon Neutrality and Eco-Environmental Technology Innovation Center of Qingdao, Qingdao 266071, China. Electronic address:
In this study, Fe-Ni-layered double hydroxide modified crayfish shell biochar substrate (Fe-Ni-LDH@CSBC) was successfully prepared and introduced into constructed wetland (CW) to research the Cr(VI) removal mechanism through substrate adsorption and microbial action. Adsorption experiments demonstrated the equilibrium adsorption capacities of Fe-Ni-LDH@CSBC for Cr(VI) could reach 1058.48 (C=10 mg/L) and 1394.
View Article and Find Full Text PDFSci Total Environ
September 2025
Laboratory of Plant Molecular Physiology, Centre of Biotechnology of Borj-Cedria, PB.901, 2050, Hammam-Lif, Tunisia. Electronic address:
Climate change is challenging agriculture and food security due to the limited adaptability of domesticated crops. While plant range shifts along latitudinal and altitudinal gradients are well-documented, their impacts on belowground microbial communities and plant adaptability remain poorly understood. Vitis vinifera subsp.
View Article and Find Full Text PDFJ Control Release
September 2025
Jiangsu Key Laboratory of Druggability of Biopharmaceuticals, Department of Pharmaceutics, China Pharmaceutical University, 639 Longmian Avenue, Nanjing 211198, PR China. Electronic address:
The tumor microenvironment (TME) is a complex and dynamic ecosystem that significantly influences tumor progression, immune modulation, and therapeutic response. A key component of the TME is the tumor-associated microbiota, which has emerged as an important player in cancer biology, affecting tumor metastasis, immune evasion, and resistance to treatments. The recent advent of high-throughput sequencing technologies has revolutionized our understanding of the microbiome, revealing distinct microbial communities across various tumor types.
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