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Unraveling the Trade-Off Effect of Pyrogenic Carbons Between Biopseudocapacitors and Bioconductors During Anaerobic Methanogenesis.
Environ Sci Technol
January 2025
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, PR China.
Pyrogenic carbons (PCs), with varying structures depending on the materials and thermal treatment conditions, have been extensively used to enhance anaerobic digestion by mediating electron transfer. However, the underlying mechanism has yet to be explored. Herein, the redirection and enhancement of the direct interspecies electron transfer (DIET) pathway were evidenced, along with the upregulated electrochemical properties and structural proteins in the methanogenic consortia.
View Article and Find Full Text PDFDiagnostic Accuracy of Artificial Intelligence for Detection of Rib Fracture on X-ray and Computed Tomography Imaging: A Systematic Review.
J Imaging Inform Med
January 2025
Department of Orthopedic Surgery, Arrowhead Regional Medical Center, Colton, CA, USA.
Rib pathology is uniquely difficult and time-consuming for radiologists to diagnose. AI can reduce radiologist workload and serve as a tool to improve accurate diagnosis. To date, no reviews have been performed synthesizing identification of rib fracture data on AI and its diagnostic performance on X-ray and CT scans of rib fractures and its comparison to physicians.
View Article and Find Full Text PDFAcute Concurrent Exercise Improves Inhibitory Control Without Mediating the Role of Lactate: An Event-Related Potential Study.
Sports Med Open
January 2025
Department of Physical Education and Sport Sciences, National Taiwan Normal University, 162, Section 1, Heping E. Road, Taipei, 106, Taiwan.
Background: Concurrent exercise (CE), an emerging exercise modality characterized by sequential bouts of aerobic (AE) and resistance exercise (RE), has demonstrated acute benefits on executive functions (EFs) and neuroelectric P3 amplitude. However, the effect of acute CE on inhibitory control, a sub-component of EFs, and P3 amplitude remains inconclusive. Moreover, exploring the mechanisms underlying the effects of acute exercise on EFs contributes to scientific comprehension, with lactate recognized as a crucial candidate positively correlated with EFs.
View Article and Find Full Text PDFForest Soil pH and Dissolved Organic Matter Aromaticity Are Distinct Drivers for Soil Microbial Community and Carbon Metabolism Potential.
Microb Ecol
January 2025
State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, China.
The ecological niche separation of microbial interactions in forest ecosystems is critical to maintaining ecological balance and biodiversity and has yet to be comprehensively explored in microbial ecology. This study investigated the impacts of soil properties on microbial interactions and carbon metabolism potential in forest soils across 67 sites in China. Using redundancy analysis and random forest models, we identified soil pH and dissolved organic matter (DOM) aromaticity as the primary drivers of microbial interactions, representing abiotic conditions and resource niches, respectively.
View Article and Find Full Text PDFExploring the role of multimodal [F]F-PSMA-1007 PET/CT and multiparametric MRI data in predicting ISUP grading of primary prostate cancer.
Eur J Nucl Med Mol Imaging
January 2025
The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
Purpose: The study explores the role of multimodal imaging techniques, such as [F]F-PSMA-1007 PET/CT and multiparametric MRI (mpMRI), in predicting the ISUP (International Society of Urological Pathology) grading of prostate cancer. The goal is to enhance diagnostic accuracy and improve clinical decision-making by integrating these advanced imaging modalities with clinical variables. In particular, the study investigates the application of few-shot learning to address the challenge of limited data in prostate cancer imaging, which is often a common issue in medical research.
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