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The role of clipping and burning in modulating soil organic carbon stability in karst ecosystems of southwest China: A stoichiometric analysis
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Green forests for bats: Response to stand-scale management interventions – Results of an experiment
No full textRegulating manufacturing FDI: Local labor market responses to a protectionist policy in Indonesia
No full texthttp://dx.doi.org/10.13039/501100001659 German Research Foundatio
Contrasting biochemical compositions and microbial interactions of English oak and black poplar root mucilage
No full texthttp://dx.doi.org/10.13039/501100009469 Conseil Régional du Centre-Val de Loir
Artifacts in photoacoustic imaging: Origins and mitigations
No full texthttp://dx.doi.org/10.13039/501100000266 Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/100006219 Kurt Weill Foundation for Musichttp://dx.doi.org/10.13039/501100014685 University of Twente TechMed Centrehttp://dx.doi.org/10.13039/501100022011 Cancer Research UK Cambridge Research Institutehttp://dx.doi.org/10.13039/501100000289 Cancer Research UKhttp://dx.doi.org/10.13039/501100001659 Deutsche Forschungsgemeinschaf
A Spatially Separated Germylene-Carbene Compound for Site-Selective Small-Molecule Activation
No full textKinetic Stabilization in Diaryl-Substituted Stannylenes: N 2 O Reactivity, Intramolecular C–H Activation, and Crystalline (Eind)Li(THF) 2 as a Versatile Precursor in Tin Chemistry
No full textSupramolecular Complexation of Quenched Rosamines with Cucurbit[7]Uril: Fluorescence Turn-ON Effect for Super-Resolution Imaging
No full textHighly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis
No full textAbstract Activity recognition in live-cell imaging is labor-intensive and requires significant human effort. Existing automated analysis tools are largely limited in versatility. We present the Intelligent Vesicle Exocytosis Analysis (IVEA) platform, an ImageJ plugin for automated, reliable analysis of fluorescence-labeled vesicle fusion events and other burst-like activity. IVEA includes three specialized modules for detecting: (1) synaptic transmission in neurons, (2) single-vesicle exocytosis in any cell type, and (3) nano-sensor-detected exocytosis. Each module uses distinct techniques, including deep learning, allowing the detection of rare events often missed by humans at a speed estimated to be approximately 60 times faster than manual analysis. IVEA’s versatility can be expanded by refining or training new models via an integrated interface. With its impressive speed and remarkable accuracy, IVEA represents a seminal advancement in exocytosis image analysis and other burst-like fluorescence fluctuations applicable to a wide range of microscope types and fluorescent dyes.Deutsche Forschungsgemeinschaft https://doi.org/10.13039/501100001659European Commission https://doi.org/10.13039/501100000780University of Saarlan