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An 11-year-old male French bulldog presented with incidental cystic lesions by the pulmonary CT. CT revealed two cysts in the right caudal lobe of the lung that were suspicious for emphysematous lesions. These cysts were divided into an air layer and a soft tissue-like layer. Dynamic computed tomography (DCT) of cysts revealed undulating motion in the soft tissue-like layer. The dog's rearing environment included brackish water, and it was evident that the dog had been eating brackish water crabs from the river. The dog was diagnosed with paragonimiasis. This DCT imaging revealed movement of live worms inside the cysts. This study is the first report that DCT may be useful for differentiating paragonimiasis from other pulmonary lesions.
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http://dx.doi.org/10.1292/jvms.25-0169 | DOI Listing |
Genome Biol
September 2025
Department of Biology, Plant-Microbe Interactions, Science for Life, Utrecht University, Utrecht, 3584CH, The Netherlands.
Background: Plant roots release root exudates to attract microbes that form root communities, which in turn promote plant health and growth. Root community assembly arises from millions of interactions between microbes and the plant, leading to robust and stable microbial networks. To manage the complexity of natural root microbiomes for research purposes, scientists have developed reductionist approaches using synthetic microbial inocula (SynComs).
View Article and Find Full Text PDFNat Microbiol
September 2025
Division of Computational Pathology, Brigham and Women's Hospital, Boston, MA, USA.
Although dynamical systems models are a powerful tool for analysing microbial ecosystems, challenges in learning these models from complex microbiome datasets and interpreting their outputs limit use. We introduce the Microbial Dynamical Systems Inference Engine 2 (MDSINE2), a Bayesian method that learns compact and interpretable ecosystems-scale dynamical systems models from microbiome timeseries data. Microbial dynamics are modelled as stochastic processes driven by interaction modules, or groups of microbes with similar interaction structure and responses to perturbations, and additionally, noise characteristics of data are modelled.
View Article and Find Full Text PDFAnn Biomed Eng
September 2025
Department of Mechanical Engineering, Koc University, Rumeli Feneri Campus, Sarıyer, 34450, Istanbul, Turkey.
Purpose: The design and development of ventricular assist devices have heavily relied on computational tools, particularly computational fluid dynamics (CFD), since the early 2000s. However, traditional CFD-based optimization requires costly trial-and-error approaches involving multiple design cycles. This study aims to propose a more efficient VAD design and optimization framework that overcomes these limitations.
View Article and Find Full Text PDFLight Sci Appl
September 2025
State Key Laboratory of Flexible Electronics, Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications (NUPT), Nanjing, 210023, China.
As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components.
View Article and Find Full Text PDFACS Nano
September 2025
Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States.
Achieving high performance nanoscale photonic functionalities remains extraordinarily challenging when using naturally derived biomaterials. The ability to manipulate ultrathin films of structural proteins─combined with photolithographic control of their polymorphism─unlocks a compelling route toward engineering biopolymer-based photonic crystals with precisely defined photonic bandgaps and reconfigurable structural colors. In this work, we describe a robust, water-based fabrication process for silk/inorganic hybrid one-dimensional (1D) photonic crystals that overcomes many of the conventional difficulties in ensuring reproducibility, uniformity, and reliability at the nanoscale.
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