Brain metastasis frequently occurs in individuals with cancer and is often fatal. We used multiphoton laser scanning microscopy to image the single steps of metastasis formation in real time. Thus, it was possible to track the fate of individual metastasizing cancer cells in vivo in relation to blood vessels deep in the mouse brain over minutes to months. The essential steps in this model were arrest at vascular branch points, early extravasation, persistent close contacts to microvessels and perivascular growth by vessel cooption (melanoma) or early angiogenesis (lung cancer). Inefficient steps differed between the tumor types. Long-term dormancy was only observed for single perivascular cancer cells, some of which moved continuously. Vascular endothelial growth factor-A (VEGF-A) inhibition induced long-term dormancy of lung cancer micrometastases by preventing angiogenic growth to macrometastases. The ability to image the establishment of brain metastases in vivo provides new insights into their evolution and response to therapies.
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http://dx.doi.org/10.1038/nm.2072 | DOI Listing |
J Particip Med
January 2025
Department of Ambulatory Care, Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Background: Health authorities worldwide have invested in digital technologies to establish robust information exchange systems for improving the safety and efficiency of medication management. Nevertheless, inaccurate medication lists and information gaps are common, particularly during care transitions, leading to avoidable harm, inefficiencies, and increased costs. Besides fragmented health care processes, the inconsistent incorporation of patient-driven changes contributes to these problems.
View Article and Find Full Text PDFOrbit
January 2025
Ruiz Department of Ophthalmology and Visual Science, McGovern Medical School at University of Texas Health Science Center, Houston, Texas, USA.
Purpose: To present a modified evisceration technique with a full-thickness horizontal sclerotomy and assess post-operative motility and long-term outcomes.
Methods: This is a retrospective chart review of patients who underwent evisceration with a single surgeon (TJM). The standard initial steps of evisceration were performed.
Digit Biomark
December 2024
VivoSense, Inc., Newport Coast, CA, USA.
Introduction: Wrist-worn accelerometers can capture stepping behavior passively, continuously, and remotely. Methods utilizing peak detection, threshold crossing, and frequency analysis have been used to detect steps from wrist-worn accelerometer data, but it remains unclear how different approaches perform across a range of walking speeds and free-living activities. In this study, we evaluated the performance of four open-source methods for deriving step counts from wrist-worn accelerometry data, when applied to data from a range of structured locomotion and free-living activities.
View Article and Find Full Text PDFSurg Endosc
January 2025
Division of General Surgery, Bariatric Unit, Tel Aviv Medical Center, Affiliated to Sackler Faculty of Medicine, Tel Aviv University, 6, Weizman St, 6423906, Tel- Aviv, Israel.
Background: Safety in one anastomosis gastric bypass (OAGB) is judged by outcomes, but it seems reasonable to utilize best practices for safety, whose performance can be evaluated and therefore improved. We aimed to test an artificial intelligence-based model in real world for the evaluation of adherence to best practices in OAGB.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.
View Article and Find Full Text PDFJ Neural Eng
January 2025
Department of Information Engineering, Electronics and Telecommunications, University of Rome La Sapienza, Piazzale Aldo Moro 5, Rome, 00185, ITALY.
Deep learning tools applied to high-resolution neurophysiological data have significantly progressed, offering enhanced decoding, real-time processing, and readability for practical applications. However, the design of artificial neural networks to analyze neural activity in vivo remains a challenge, requiring a delicate balance between efficiency in low-data regimes and the interpretability of the results. Approach: To address this challenge, we introduce a novel specialized transformer architecture to analyze single-neuron spiking activity.
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