Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Oxford University Press (OUP)  

Abstract

Morphogenesis is a developmental process of organisms being shaped through complex and cooperative cellular movements. To understand the interplay between genetic programs and the resulting multicellular morphogenesis, it is essential to characterize the morphologies and dynamics at the single-cell level and to understand how physical forces serve as both signaling components and driving forces of tissue deformations. In recent years, advances in microscopy techniques have led to improvements in imaging speed, resolution and depth. Concurrently, the development of various software packages has supported large-scale, analyses of challenging images at the single-cell resolution. While these tools have enhanced our ability to examine dynamics of cells and mechanical processes during morphogenesis, their effective integration requires specialized expertise. With this background, this review provides a practical overview of those techniques. First, we introduce microscopic techniques for multicellular imaging and image analysis software tools with a focus on cell segmentation and tracking. Second, we provide an overview of cutting-edge techniques for mechanical manipulation of cells and tissues. Finally, we introduce recent findings on morphogenetic mechanisms and mechanosensations that have been achieved by effectively combining microscopy, image analysis tools and mechanical manipulation techniques.

DOI： 10.1093/jmicro/dfad059

Web of Science

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CiNii Research

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Other Link： https://academic.oup.com/jmicro/article-pdf/73/3/226/58122776/dfad059.pdf

Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Cold Spring Harbor Laboratory  

Motivation

Particle tracking is an important step of analysis in a variety of scientific fields, and is particularly indispensable for the construction of cellular lineages from live images. Although various supervised machine learning methods have been developed for cell tracking, the diversity of the data still necessitates heuristic methods that require parameter estimations from small amounts of data. For this, solving tracking as a linear assignment problem (LAP) has been widely applied and demonstrated to be efficient. However, there has been no implementation that allows custom connection costs, parallel parameter tuning with ground truth annotations, and the functionality to preserve ground truth connections, limiting the application to datasets with partial annotations.

Results

We developed LapTrack, a LAP-based tracker which allows including arbitrary cost functions and inputs, parallel parameter tuning, and ground-truth track preservation. Analysis of real and artificial datasets demonstrates the advantage of custom metric functions for tracking score improvement. The tracker can be easily combined with other Python-based tools for particle detection, segmentation, and visualization.

Availability and implementation

LapTrack is available as a Python package on PyPi, and the notebook examples are shared at https://github.com/yfukai/laptrack. The data and code for this publication are hosted at https://github.com/NoneqPhysLivingMatterLab/laptrack-optimization.

Contact

ysk@yfukai.net

DOI： 10.1093/bioinformatics/btac799

Web of Science

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Publishing type：Research paper (scientific journal)   Publisher：{American Physical Society}  

The nonequilibrium steady state of the one-dimensional (1D)
Kardar-Parisi-Zhang (KPZ) universality class is studied in-depth by exact
solutions, yet no direct experimental evidence of its characteristic
statistical properties has been reported so far. This is arguably because, for
an infinitely large system, infinitely long time is needed to reach such a
stationary state and also to converge to the predicted universal behavior. Here
we circumvent this problem in the experimental system of growing liquid-crystal
turbulence, by generating an initial condition that possesses a long-range
property expected for the KPZ stationary state. The resulting interface
fluctuations clearly show characteristic properties of the 1D stationary KPZ
interfaces, including the convergence to the Baik-Rains distribution. We also
identify finite-time corrections to the KPZ scaling laws, which turn out to
play a major role in the direct test of the stationary KPZ interfaces. This
paves the way to explore unsolved properties of the stationary KPZ interfaces
experimentally, making possible connections to nonlinear fluctuating
hydrodynamics and quantum spin chains as recent studies unveiled relation to
the stationary KPZ.

DOI： 10.1103/PhysRevLett.124.250602

arXiv

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Other Link： http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevLett.124.250602/fulltext

Publishing type：Doctoral thesis  

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Authorship：Lead author,　Corresponding author   Publishing type：Research paper (scientific journal)   Publisher：American Physical Society ({APS})  

We study the $(1+1)$-dimensional Kardar-Parisi-Zhang (KPZ) interfaces growing
inward from ring-shaped initial conditions, experimentally and numerically,
using growth of a turbulent state in liquid-crystal electroconvection and an
off-lattice Eden model, respectively. To realize the ring initial condition
experimentally, we introduce a holography-based technique that allows us to
design the initial condition arbitrarily. Then, we find that fluctuation
properties of ingrowing circular interfaces are distinct from those for the
curved or circular KPZ subclass and, instead, are characterized by the flat
subclass. More precisely, we find an asymptotic approach to the Tracy-Widom
distribution for the Gaussian orthogonal ensemble and the $\text{Airy}_1$
spatial correlation, as long as time is much shorter than the characteristic
time determined by the initial curvature. Near this characteristic time,
deviation from the flat KPZ subclass is found, which can be explained in terms
of the correlation length and the circumference. Our results indicate that the
sign of the initial curvature has a crucial role in determining the universal
distribution and correlation functions of the KPZ class.

DOI： 10.1103/PhysRevLett.119.030602

PubMed

arXiv

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Event date： 2025.11

Language：English   Presentation type：Oral presentation (general)  

Venue：RIKEN IMS Yokohama Campus, Yokohama, Japan   Country：Japan  

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Event date： 2025.11

Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：Kyoto International Conference Center, Kyoto, Japan   Country：Japan  

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Event date： 2025.10

Language：English   Presentation type：Poster presentation  

Venue：RIKEN Center for Biosystems Dynamics Research, Kobe, Japan   Country：Japan  

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Event date： 2025.10

Language：English   Presentation type：Poster presentation  

Venue：Kudan Kaikan Terrace, Tokyo, Japan   Country：Japan  

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Event date： 2025.3

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：Kyoto University   Country：Japan  

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Event date： 2025.3

Language：English   Presentation type：Poster presentation  

Venue：RIKEN Center for Biosystems Dynamics Research   Country：Japan  

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Event date： 2024.11

Language：English   Presentation type：Poster presentation  

Venue：Fukuoka International Congress Center & Marin Messe Fukuoka   Country：Japan  

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Event date： 2024.11

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：Chiba University   Country：Japan  

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Event date： 2024.10

Language：English   Presentation type：Poster presentation  

Venue：Plaza Verde   Country：Japan  

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Event date： 2024.9

Language：English   Presentation type：Oral presentation (general)  

Venue：Kyoto University   Country：Japan  

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Event date： 2019.7

Language：English   Presentation type：Oral presentation (general)  

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Language：Japanese