3-D Worm Tracker for Freely Moving <em>C. elegans</em>

<div><p>The manner in which the nervous system regulates animal behaviors in natural environments is a fundamental issue in biology. To address this question, <i>C. elegans</i> has been widely used as a model animal for the analysis of various animal behaviors. Previous behavioral assays have been limited to two-dimensional (2-D) environments, confining the worm motion to a planar substrate that does not reflect three-dimensional (3-D) natural environments such as rotting fruits or soil. Here, we develop a 3-D worm tracker (3DWT) for freely moving <i>C. elegans</i> in 3-D environments, based on a stereoscopic configuration. The 3DWT provides us with a quantitative trajectory, including the position and movement direction of the worm in 3-D. The 3DWT is also capable of recording and visualizing postures of the moving worm in 3-D, which are more complex than those in 2-D. Our 3DWT affords new opportunities for understanding the nervous system function that regulates animal behaviors in natural 3-D environments.</p> </div

The principle of the 3-D worm tracker (3DWT).

<p>(A) Experimental scheme of the stereoscopic recording. Two imaging assemblies at right angles with the same focal point are used to synchronously record images of <i>C. elegans</i> from two perpendicular directions. (B) Stereomatching of skeletons. The two X-Z and Y-Z skeletons, extracted from the two projection images of the worm, are combined using stereomatching to reconstruct the 3-D skeleton. (C) Volume rendering of the 3-D skeleton. The 3-D volume of the worm is rendered by assigning particles that are centered on the 3D skeleton points.</p

Bending vector analysis of worm motion.

<p>(A) Schematic of the bending vector in a 3-D skeleton. The arrows indicate the bending vector at a skeletal point, P_i. (B) Variable bending vectors of a second skeletal point from the head of a representative worm during crawling. (C) The X-Y projections of bending vectors along the whole body for 5.5 s of crawling. The colors of arrows represent the directions of the bending vectors by linearly converting the components of normalized bending vectors (−1.0∼1.0) to 8-bit colors (0∼255): the X-component is displayed in red (R), the Y-component in green (G), and the Z-component in blue (B).</p

3-D trajectory and velocity of a worm.

<p>(A) 3-D trajectory of the worm. Red, blue, and green arrows are movement directions of a worm for 12 s, 14 s, and 12 s, respectively. (B) The x-, y-, and z-components of the worm's velocity.</p

Volume-rendered images in three views.

<p>(A) 3-D posture of a worm showing bends in various directions (gray arrows) with only slight changes in the moving direction (green arrow) during crawling. (B) 3-D posture of another worm showing a significant change in the moving direction (green arrow). The asterisk in each image indicates the head of the worm.</p

Three-Dimensional Writing of Highly Stretchable Organic Nanowires

Three-dimensional (3D) writing is a promising approach to realize stretchable electronics, but is so far limited to microscale features. We developed accurate 3D writing for highly stretchable organic nanowire arrays using a nanoscale polymer meniscus. Specifically, 3D nanoarches of poly­(3,4-ethylenedioxythiophene)/poly­(styrenesulfonate) with unprecedented stretchability, over 270%, and no compromise on the electrical characteristics were fabricated. Then, we integrated nanoarches into photoswitches, electrochemical transistors, and electrical interconnects. The impact of these successful tests goes well beyond these specific devices and opens the way to new classes of stretchable nanodevices based on organic materials

Flexible Strain Sensors Fabricated by Meniscus-Guided Printing of Carbon Nanotube–Polymer Composites

Printed strain sensors have promising potential as a human–machine interface (HMI) for health-monitoring systems, human-friendly wearable interactive systems, and smart robotics. Herein, flexible strain sensors based on carbon nanotube (CNT)–polymer composites were fabricated by meniscus-guided printing using a CNT ink formulated from multiwall nanotubes (MWNTs) and polyvinylpyrrolidone (PVP); the ink was suitable for micropatterning on nonflat (or curved) substrates and even three-dimensional structures. The printed strain sensors exhibit a reproducible response to applied tensile and compressive strains, having gauge factors of 13.07 under tensile strain and 12.87 under compressive strain; they also exhibit high stability during ∼1500 bending cycles. Applied strains induce a contact rearrangement of the MWNTs and a change in the tunneling distance between them, resulting in a change in the resistance (Δ<i>R</i>/<i>R</i>₀) of the sensor. Printed MWNT–PVP sensors were used in gloves for finger movement detection; these can be applied to human motion detection and remote control of robotic equipment. Our results demonstrate that meniscus-guided printing using CNT inks can produce highly flexible, sensitive, and inexpensive HMI devices

Flexible Strain Sensors Fabricated by Meniscus-Guided Printing of Carbon Nanotube–Polymer Composites

Printed strain sensors have promising potential as a human–machine interface (HMI) for health-monitoring systems, human-friendly wearable interactive systems, and smart robotics. Herein, flexible strain sensors based on carbon nanotube (CNT)–polymer composites were fabricated by meniscus-guided printing using a CNT ink formulated from multiwall nanotubes (MWNTs) and polyvinylpyrrolidone (PVP); the ink was suitable for micropatterning on nonflat (or curved) substrates and even three-dimensional structures. The printed strain sensors exhibit a reproducible response to applied tensile and compressive strains, having gauge factors of 13.07 under tensile strain and 12.87 under compressive strain; they also exhibit high stability during ∼1500 bending cycles. Applied strains induce a contact rearrangement of the MWNTs and a change in the tunneling distance between them, resulting in a change in the resistance (Δ<i>R</i>/<i>R</i>₀) of the sensor. Printed MWNT–PVP sensors were used in gloves for finger movement detection; these can be applied to human motion detection and remote control of robotic equipment. Our results demonstrate that meniscus-guided printing using CNT inks can produce highly flexible, sensitive, and inexpensive HMI devices

Flexible Strain Sensors Fabricated by Meniscus-Guided Printing of Carbon Nanotube–Polymer Composites

Printed strain sensors have promising potential as a human–machine interface (HMI) for health-monitoring systems, human-friendly wearable interactive systems, and smart robotics. Herein, flexible strain sensors based on carbon nanotube (CNT)–polymer composites were fabricated by meniscus-guided printing using a CNT ink formulated from multiwall nanotubes (MWNTs) and polyvinylpyrrolidone (PVP); the ink was suitable for micropatterning on nonflat (or curved) substrates and even three-dimensional structures. The printed strain sensors exhibit a reproducible response to applied tensile and compressive strains, having gauge factors of 13.07 under tensile strain and 12.87 under compressive strain; they also exhibit high stability during ∼1500 bending cycles. Applied strains induce a contact rearrangement of the MWNTs and a change in the tunneling distance between them, resulting in a change in the resistance (Δ<i>R</i>/<i>R</i>₀) of the sensor. Printed MWNT–PVP sensors were used in gloves for finger movement detection; these can be applied to human motion detection and remote control of robotic equipment. Our results demonstrate that meniscus-guided printing using CNT inks can produce highly flexible, sensitive, and inexpensive HMI devices

Flexible Strain Sensors Fabricated by Meniscus-Guided Printing of Carbon Nanotube–Polymer Composites

Printed strain sensors have promising potential as a human–machine interface (HMI) for health-monitoring systems, human-friendly wearable interactive systems, and smart robotics. Herein, flexible strain sensors based on carbon nanotube (CNT)–polymer composites were fabricated by meniscus-guided printing using a CNT ink formulated from multiwall nanotubes (MWNTs) and polyvinylpyrrolidone (PVP); the ink was suitable for micropatterning on nonflat (or curved) substrates and even three-dimensional structures. The printed strain sensors exhibit a reproducible response to applied tensile and compressive strains, having gauge factors of 13.07 under tensile strain and 12.87 under compressive strain; they also exhibit high stability during ∼1500 bending cycles. Applied strains induce a contact rearrangement of the MWNTs and a change in the tunneling distance between them, resulting in a change in the resistance (Δ<i>R</i>/<i>R</i>₀) of the sensor. Printed MWNT–PVP sensors were used in gloves for finger movement detection; these can be applied to human motion detection and remote control of robotic equipment. Our results demonstrate that meniscus-guided printing using CNT inks can produce highly flexible, sensitive, and inexpensive HMI devices