A long-standing question in natural reproduction is how mammalian sperm navigate inside female reproductive tract and finally reach the egg cell, or oocyte. Recently, fluid flow was proposed as a long–range guidance cue for sperm navigation. Coitus induces fluid flow from oviduct to uterus, and sperm align themselves against the flow direction and swim upstream, a phenomenon termed rheotaxis. Whether sperm rheotaxis is a passive process dominated by fluid mechanics, or sperm actively sense and adapt to fluid flow remains controversial. Here we report the first quantitative study of sperm flagellar motion during human sperm rheotaxis and provide direct evidence indicating that sperm rheotaxis is a passive process. Experimental results show that there is no significant difference in flagellar beating amplitude and asymmetry between rheotaxis-turning sperm and those sperm swimming freely in the absence of fluid flow. Additionally, fluorescence image tracking shows no Ca2+ influx during sperm rheotaxis turning, further suggesting there is no active signal transduction during human sperm rheotaxis.
A scanning electron microscope (SEM) provides real-time imaging with nanometer resolution and a large scanning area, which enables the development and integration of robotic nanomanipulation systems inside a vacuum chamber to realize simultaneous imaging and direct interactions with nanoscaled samples. Emerging techniques for nanorobotic manipulation during SEM imaging enable the characterization of nanomaterials and nanostructures and the prototyping/assembly of nanodevices. This paper presents a comprehensive survey of recent advances in nanorobotic manipulation, including the development of nanomanipulation platforms, tools, changeable toolboxes, sensing units, control strategies, electron beam-induced deposition approaches, automation techniques, and nanomanipulation-enabled applications and discoveries. The limitations of the existing technologies and prospects for new technologies are also discussed.
A passage on page five contained a number of typographical errors. These errors affected the chemical formulae contained therein. The corrected passage is as follows:For Na 2 S-P 2 S 5 complex, the main peaks at 386 and 418 cm −1 correspond to the presence of edge-shared P 2 short-range order (SRO) group (PS 3 − ), indicating the formation of branching network of Na-P-S (Na:P = 1:1), [42−44,46−48] while the main peak at 482 cm −1 is ascribed to the existence of S-S bond. [46−48] As to the prepassivated Na, the three shoulders and one peak appearing at 380, 403, 424, and 462 cm −1 can be ascribed to the presence of P 1P SRO group (P 2 S 6 4− ) and P 1 SRO group (P 2 S 7 4− ) as molecular anion or terminating unit (Na:P = 2:1), as well as P 0 SRO group (PS 4 3− ) as isolated tetrahedra (Na:P = 3:1). [46][47][48] Thus, the Raman spectrum of the Na surface after passivation indicates that the amorphous Na-P-S protection layer possibly consists of Na 3 PS 4 , Na 4 P 2 S 7 , and Na 4 P 2 S 6 on metallic Na due to the reaction between Na-P-S complex and Na. Meanwhile, the P 2 group peak at 386 cm −1 slightly shifts to 390 cm −1 and the peak for the S-S bond disappears, indicating the disintegration of P 2 SRO branching network when forming the Na-P-S passivation layer.The authors apologize for any inconvenience that this mistake may have caused.
Compared to robotic injection of suspended cells (e.g., embryos and oocytes), fewer attempts were made to automate the injection of adherent cells (e.g., cancer cells and cardiomyocytes) due to their smaller size, highly irregular morphology, small thickness (a few micrometers thick), and large variations in thickness across cells. This paper presents a robotic system for automated microinjection of adherent cells. The system is embedded with several new capabilities: automatically locating micropipette tips; robustly detecting the contact of micropipette tip with cell culturing surface and directly with cell membrane; and precisely compensating for accumulative positioning errors. These new capabilities make it practical to perform adherent cell microinjection truly via computer mouse clicking in front of a computer monitor, on hundreds and thousands of cells per experiment (versus a few to tens of cells as state of the art). System operation speed, success rate, and cell viability rate were quantitatively evaluated based on robotic microinjection of over 4000 cells. This paper also reports the use of the new robotic system to perform cell-cell communication studies using large sample sizes. The gap junction function in a cardiac muscle cell line (HL-1 cells), for the first time, was quantified with the system.
Abstract-In robotic micromanipulation, end-effector tips must be first located under microscopy imaging before manipulation is performed. The tip of micromanipulation tools is typically a few micrometers in size and highly delicate. In all existing micromanipulation systems, the process of locating the end-effector tip is conducted by a skilled operator, and the automation of this task has not been attempted. This paper presents a technique to automatically locate end-effector tips. The technique consists of programmed sweeping patterns, motion history image end-effector detection, active contour to estimate end-effector positions, autofocusing and quad-tree search to locate an end-effector tip, and, finally, visual servoing to position the tip to the center of the field of view. Two types of micromanipulation tools (micropipette that represents single-ended tools and microgripper that represents multiended tools) were used in experiments for testing. Quantitative results are reported in the speed and success rate of the autolocating technique, based on over 500 trials. Furthermore, the effect of factors such as imaging mode and image processing parameter selections was also quantitatively discussed. Guidelines are provided for the implementation of the technique in order to achieve high efficiency and success rates.
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