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Biology subjects

Nagai, T.

Publications and source records attributed to Nagai, T..

3 recordsLinked to original sources

In vivo brain activity imaging of interactively locomoting mice

Electrophysiological field potential dynamics have been widely used to investigate brain functions and related psychiatric disorders. Conversely, however, various technical limitations of conventional recording methods have limited its applicability to freely moving subjects, especially when they are in a group and socially interacting with each other. Here, we propose a new method to overcome these technical limitations by introducing a bioluminescent voltage indicator called LOTUS-V. Using our simple and fiber-free recording method, named \"SNIPA,\" we succeeded in capturing brain activity in freely-locomotive mice, without the need for complicated instruments. This novel method further allowed us to simultaneously record from multiple independently-locomotive animals that were interacting with one another. Further, we successfully demonstrated that the primary visual cortex was activated during the interaction. This methodology will further facilitate a wide range of studies in neurobiology and psychiatry.

neuroscience

A spontaneously blinking fluorescent protein for simple single laser super-resolution live cell imaging

Super-resolution imaging techniques based on single molecule localization microscopy (SMLM) broke the diffraction limit of optical microscopy in living samples with the aid of photoswitchable fluorescent probes and intricate microscopy systems. Here, we developed a fluorescent protein, SPOON, which can be switched-off by excitation light illumination and switched-on by thermally-induced dehydration resulting in an apparent spontaneous blinking behavior. This unique property of SPOON provides a simple SMLM-based super-resolution imaging platform which requires only a single 488 nm laser.

biophysics

Concept and in-silico assessment of an algorithm for monitoring cytosolic fluorescent aggregates in cells.

Autophagy is an evolutionary conserved pathway, by which eukaryotic cells degrade long-living cellular proteins and intracellular organelles, to maintain a pool of available nutrients. Impaired autophagy has been associated to important pathophysiological conditions, and this is the reason why several techniques have been developed for its correct assessment and monitoring. Fluorescence microscopy is one of these tools, which relies on the detection of specific fluorescence changes of targeted GFP-based reporters in dot-like organelles in which autophagy is executed. Currently, several procedures exist to count and segment this punctate structures in the resulting fluorescence images, however, they are either based on subjective criteria, or no information is available related to them. Here we present the concept of an algorithm for a semi-automatic detection and segmentation in 2D fluorescence images of spot-like structures similar to those observed under induction of autophagy. By evaluating the algorithm on more than 20000 simulated images of cells containing a variable number of punctate structures of different sizes and different levels of applied noise, we demonstrate its high robustness of puncta detection, even on a high noise background. We further demonstrate this feature of our algorithm by testing it in experimental conditions of a high non-specific background signal. We conclude that our algorithm is a suitable tool to be tested in biologically-relevant contexts.

bioinformatics